Exploring the History, Impact, and Potential of Artificial Intelligence #AI

Summarise this content to 300 words

While I might not cover every single detail of AI’s past, present, and future (I’m not trying to be a Wikipedia here!), this article will give you an exciting look into the world of AI. After months of research, I finally started writing this a few weeks ago. Some information might be outdated, and some parts might be overly detailed, but if you have any feedback or want to contribute, feel free to reach out. So, please keep reading to dive deep into the tech and uncover some cool insights to help you unleash its full potential.

Artificial intelligence (AI) technology is advancing rapidly, revolutionizing numerous aspects of modern life. There are new announcements almost every day, with big players like Meta, Google, and Microsoft competing to get an edge over consumers.

AI started gaining significant popularity in the late 2010s and early 2020s, especially after the unveiling of ChatGPT in late 2022, which impressed and sometimes frightened people with its capabilities, leading to rapid development in the realm of Large Language Models (LLMs), often referred to as Generative AI. Following this, Google introduced their chatbot, Bard (now known as Gemini).

Meanwhile, numerous smaller applications began integrating AI features into their business models. For instance, Canva, Capcut, Grammarly, Notion, Adobe’s Firefly and Generative Fill, eBay, Snapchat, Spotify, and many more applications that we use daily have adopted AI capabilities. Also, guess what? AI chatbots have started replacing traditional customer care on websites.

Moreover, many free-to-use services have introduced paid plans powered by AI, indicating that while we might be thinking on a small scale, the topic is vast and has been improving for years. Life is moving fast, and we’re transitioning through many phases, like the trend of Zoom and video calls during the pandemic and now the rise of AI.

Are we in a bubble? Will AI technology change the world as dramatically as the internet did, or will it fizzle out and leave us with some advancements but not a new global economy? (The answer is obvious now, don’t you think?)

Before we dive into several areas where AI is making waves, let’s first understand the basics of AI.

Artificial intelligence (AI) allows computers to learn and solve problems almost like a person. AI systems are trained on huge amounts of information and learn to identify patterns to carry out tasks such as having human-like conversations or predicting a product an online shopper might buy.

Nowadays, AI’s capabilities are not just limited to text prompting but also extend to generating images, videos, and audio. So, what are AI programs like ChatGPT and Microsoft Copilot? These are examples of what is called “Generative” AI. These programs learn from vast quantities of data, such as online text and images, to generate new content that feels like it has been made by a human. They analyze patterns, context, and nuances in language to generate responses that mimic human conversation. When a user inputs a question or prompt, the AI processes this input and generates a coherent, contextually appropriate response based on its training data (and sometimes, we end up acting like chatbots ourselves).

Other AI programs like Midjourney can create images from simple text instructions. Generative AI can also make videos and even produce music in the style of famous musicians. Recently, I discovered a new Gen AI developed by ElevenLabs, which lets you generate text-to-sound effects, a crucial turning point in content creation.

Before all these recent advancements, it’s important to acknowledge that many products have used AI for quite some time. For instance, recommendation systems, targeted advertising, increasing internet engagement, virtual assistants, voice changers, spam filtering, music production, language translation, facial recognition, biometrics, video games, social media, and search engines have all employed some form of AI. These earlier implementations were limited in functionality and were primarily based on basic Machine Learning algorithms, which had a more restricted scope and capability.

Early AI applications included simpler machine learning techniques and were often marketed with an AI badge to attract attention. This approach has been around for a long time, even in smartphone cameras and filters.

The buzz around ML and AI has only recently started growing significantly. Despite claims that OpenAI might be underperforming compared to other models and major companies, the widespread adoption of AI features in various services has led to its rapid integration into the current generation of products. It’s important to note that the AI invasion into the market began much earlier, with tech giants initially building and refining ML models for various applications.

A notable early application of AI was the development of virtual assistants such as Cortana, Google Assistant, Siri, and Alexa. These virtual assistants were seen as revolutionary at the time, enabling voice commands and providing assistance with various tasks. I see these technologies as laying the groundwork for more advanced AI developments.

After a period of developing and implementing these limited AI technologies, which most of us were using, research projects eventually brought advanced innovations to market. These included Self-Driving cars, generative AI, powerful AR/VR technology, robotic advancements, powerful speech and audio processing, sophisticated recommendation systems, etc.

Additionally, some services and features were developed and introduced only after products like GPT were launched, enabling other companies to leverage GPT and build their own AI capabilities alongside generative AI to make it even more powerful. How were these advancements possible within a relatively short period of 2–5 years, despite involving years of research?

You can skip this if you want, but for those interested in the technical details:

The rapid advancements in AI over the past decade can be attributed to several key factors. Significant breakthroughs in deep learning, particularly with neural network architectures like CNNs, RNNs, and Transformers, have greatly improved AI capabilities. The increase in computational power through GPUs, TPUs, and specialized hardware has enabled the training of complex models. The availability of massive datasets, facilitated by advances in data collection and processing, has further enhanced AI’s effectiveness. Algorithmic improvements have boosted model performance, such as backpropagation, optimization techniques, and regularization methods like dropout and batch normalization. Collaborative research, open-source initiatives, and substantial investment from tech giants have made powerful AI tools more accessible and accelerated innovation. The community’s embrace of open-source principles has fostered widespread adoption and application across industries. As a result, AI development has become more straightforward and accessible since research projects were introduced to the public. These earlier systems had limited capabilities compared to modern AI. While they demonstrated AI’s potential, they lacked the sophistication and power of today’s technologies. Referring to them as early-stage ML and DL models might be more accurate. This distinction highlights the significant advancements in recent years. However, the definition and potential of AI are still evolving.

That’s enough cool stuff about the basics to understand AI. Now, let’s talk about some of the most popular tech giants, which are household names heavily invested in AI research and development. They integrate AI across various products and services, leading the charge in the AI race.

It’s a bit complicated to talk about them individually, and some other companies might come up in the discussion, so I’ll be covering this topic here and there.

Alphabet Inc. (Google)

Speaking of Alphabet Inc., it has been at the forefront of AI development, consistently launching successful AI products. Alphabet’s AI initiatives span across various domains, including autonomous driving with Waymo, healthcare with DeepMind, and everyday applications through Google’s AI products. These ventures highlight Alphabet’s commitment to integrating AI into practical, real-world applications that benefit users and industries alike.

Google has developed its language model as a rival to well-known chatbots and capable LLMs like OpenAI’s GPT-4. Despite some sources suggesting that ChatGPT underperformed, Google has been a major player in AI research and development. In general, both Gemini Advanced and ChatGPT-4 are closely matched in performance, but here, I’m focusing on everyday tasks and the convenience of having conversations.

From the early research project Meena (now LaMDA) to PaLM AI, and then to Bard and now Gemini, Google has a long history of AI advancements, even before OpenAI gained popularity. This development has been driven by research subsidiaries like Google AI and DeepMind Technologies (formerly Google Brain).

In 2016, Google introduced Google Assistant (replacing Google Now), bringing AI-powered voice interaction to millions of users. With the power of current AI tech, Google Assistant is poised to evolve and soon be powered by Gemini, enabling more natural, nuanced, and informative interactions. This shift exemplifies Google’s response to other AI rivals and anticipates a future where Large Language Models (LLMs) like Gemini and generative chatbots revolutionize our interaction with technology. One of Google’s key strengths in AI lies in its focus on multilingual capabilities, which ensures that Google’s AI models can communicate and understand information across a vast array of languages.

In recent weeks, the AI competition between OpenAI and Google’s DeepMind has been intense. Both companies have made impressive updates, showcasing how rapidly the technology is being rolled out, echoing fears previously voiced that AI could harm society and should be paused until better understood.

Competition between the two companies heated up when Google’s DeepMind released updates to its chatbot Gemini shortly after OpenAI’s event. At Google’s I/O developer conference, they announced significant updates to Gemini, including a new competitor to Sora, advanced AI agents, and several other features. They also introduced a lightweight, text-to-text LLM called ‘Gemma’ and demonstrated Gemini’s capabilities to use personal information for tasks like holiday planning and quick itinerary building.

Google’s breakthrough in large language models is significant. A new paper by researchers at Google claims to provide LLM stability for working with text of infinite length. The paper introduces “infinite attention,” a technique configuring language models to extend their context window while keeping memory and compute requirements constant.

Google has also announced a significant update to its search engine by introducing the Search Generative Experience (SGE), where AI will summarise search results. The Gemini AI model family has also introduced Gemini 1.5 Flash for speed and efficiency, Gemini 1.5 Pro with enhanced performance and a 2 million token context window, and Gemini Nano with multimodal input support. The next-generation Gemma 2 models focus on responsible AI innovation, and Project Astra aims to develop advanced AI assistants for more natural and proactive interactions.

It has launched numerous AI tools under various names, including Duet AI for its Workspace, Veo, and Videopoet for generating videos, and they’re integrating 3D models into its map application as well.

Google is also integrating AI into all its applications, including YouTube, which is one of the company’s main sources of income. YouTube has seen significant AI advancements, such as AI-generated video backgrounds, a new editing app with audio cleanup, auto-captions, and royalty-free music, which is currently in the beta version. Additionally, there’s a conversational AI tool that provides answers and recommendations without interrupting playback, as well as AI-powered brainstorming tools in YouTube Studio.

OpenAI

Now, let’s move to OpenAI, a non-profit research company that has developed powerful AI tools and significantly contributed to the AI landscape. In fact, thhe very first Generative AI-Language Model (LLM) was the Generative Pre-trained Transformer (GPT).

Recently, OpenAI held its first-ever live session and announced its new model, GPT-4o, which claims to be “much faster” and improves capabilities across text, vision, and audio. A version of it will be free to users, but a paid version will have five times the capacity limits. The most interesting development of the company is the voice assistant, which can generate content or understand commands in voice, text, or image and perform live translations. It can also respond in real-time and observe body motion. In summary, GPT-4o promises to revolutionize the AI assistant game with features like visual assistance, real-time translation, meeting assistance, voice emotion recognition, 3D object synthesis, and comprehensive meeting notes.

Additionally, OpenAI has introduced Sora, a groundbreaking text-to-video model. Sora can generate up to minute-long videos from text prompts, offering high visual quality and adherence to user specifications.

However, OpenAI did not stop there with announcements and partnerships. The company signed a deal for access to content from Reddit to bring AI-powered features to the platform, similar to Google’s move. On the same day, Sony sent letters to OpenAI, Google, and Microsoft, asking if they had used its songs to develop their AI systems, highlighting the growing concerns over copyright issues with generative AI firms. Moreover, the company, founded by the former co-founder of OnePlus, Nothing, announced ChatGPT integration across all its audio devices powered by OpenAI’s GPT-4o. This means users can interact with OpenAI’s flagship AI model across their ecosystem.

Microsoft

Microsoft, always known for making strategic moves (or just buying out the competition), has also been a pioneer in building AI services. In a classic Microsoft fashion, they acquired OpenAI and rebranded it as Copilot, seamlessly integrating AI across its apps and services. It’s almost like they went, “Hey, why build when you can buy and rename?”

In 2019, Microsoft partnered with OpenAI, investing billions of dollars into the organization. OpenAI systems have since run on an Azure-based supercomputing platform from Microsoft. In September 2020, Microsoft announced that it had exclusively licensed OpenAI’s GPT-3, giving it sole access to the underlying model.

Fast forward to November 2022, OpenAI launched ChatGPT, a chatbot based on the GPT-3 family of LLMs. This chatbot quickly gained worldwide attention, becoming a viral internet sensation. Then, on January 23, 2023, Microsoft announced a multi-year $10 billion investment in OpenAI. Amidst fears that ChatGPT could threaten Google’s dominance as a go-to source for information, Google’s announcement was perceived as rushed to preempt Microsoft’s planned unveiling of Copilot.

Microsoft Copilot, a chatbot developed by Microsoft, was launched on February 7, 2023. It can cite sources, create poems, and write songs, replacing the discontinued Cortana. Initially introduced as Bing Chat for Microsoft Bing and Microsoft Edge, the Copilot branding was unified across Microsoft’s chatbot products throughout 2023. At its Build 2023 conference, Microsoft announced plans to integrate Copilot into Windows 11, allowing access directly through the taskbar. By January 2024, a dedicated Copilot key was announced for Windows keyboards.

Like other chatbots, Copilot utilizes generative AI, specifically the Microsoft Prometheus model, built upon OpenAI’s GPT-4 foundational large language model. This model has been fine-tuned using both supervised and reinforcement learning techniques. Copilot’s conversational interface style resembles ChatGPT and supports numerous languages and dialects.

Microsoft operates Copilot on a freemium model, providing most features for free while offering priority access to new features, including custom chatbot creation, to paid subscribers under the “Microsoft Copilot Pro” service. The free version includes several default chatbots, such as the standard Copilot chatbot and Microsoft Designer, which uses Image Creator to generate images based on text prompts.

Reports suggest that Microsoft Copilot Pro integrates seamlessly with various Microsoft products, which is considered better than GPT and Google Gemini. For instance, Outlook helps users stay on top of emails, and Copilot in Teams makes every meeting productive. Users can turn proposals into presentations, generate professional-looking documents, analyze sales results, and more with simple instructions to Copilot. (Doesn’t this sound familiar to Apple Intelligence? Wake up, fam!)

Recently, Microsoft added an official Copilot bot within the messaging app Telegram, allowing users to search, ask questions, and converse with the AI chatbot. Copilot for Telegram is currently in beta but is free for Telegram users on mobile or desktop.

And who knows? Maybe they’ll integrate Copilot with LinkedIn next. Imagine the professional networking possibilities beyond “Thrilled to announce”! (LinkedIn has already been active in that area. It launched a suite of OpenAI-powered tools in October 2023, adding reading and writing tools one month later, as well as tools to help with writing profiles, recruitment ads, and company pages.)

We’ve seen the evolution from cell phones to feature phones and then to smartphones. Now, the era of ‘IntelliPhones’ is on the horizon. The CEO of Nothing pointed out that smartphones are poised to become the AI gadgets of the future, fundamentally changing how we use these devices. He also revealed that the Nothing Phone (3), set to launch next year, will be a significant milestone in the company’s consumer AI journey.

Following that, in a recent Microsoft Surface event, they announced the first-ever AI PC, which claims to have 58% better multi-threaded performance than the latest MacBook Air. This AI PC, powered by OpenAI’s GPT-4 Turbo, offers real-time conversations, co-creation with AI-powered image creation and editing, live translation, and significantly enhanced performance. The AI computational power of the GPU and NPU delivers over 40 trillion operations per second, making it 20 times more powerful and 100 times more efficient for AI tasks.

However, this raises concerns about privacy and data protection. Organizations are expected to be transparent with users about how their data is being used and must assess and mitigate risks to people’s rights and freedoms before bringing products to market. There are ongoing inquiries with Microsoft to understand the safeguards in place to protect user privacy, particularly regarding their AI-powered features.

In recent months, Google, OpenAI, and Microsoft have faced significant challenges and controversies with their AI implementations. Due to inaccuracies, Google had to roll back its AI Overviews search tool, leading to user frustration and reliability concerns. OpenAI faced backlash over a voice feature in ChatGPT that closely resembled actress Scarlett Johansson’s voice, raising significant concerns about voice ownership and consent. Additionally, Microsoft faced criticism for its “Recall” feature, which automatically screenshots user activity on PCs. This feature was labelled a cybersecurity disaster, leading to a major privacy uproar and highlighting the critical need for robust privacy safeguards.

Over the years, Microsoft has built increasingly powerful AI systems with massive computing power. Kevin Scott, CPO of Microsoft, used marine wildlife to illustrate their scale without mentioning the specific compute numbers. In 2020, Microsoft built its first AI supercomputer for OpenAI, which trained GPT-3. Kevin compared its size to a shark. In 2022, they created a larger system for GPT-4, likening it to an orca. Recently, they deployed an even bigger system comparable to a whale. This whale-sized supercomputer is now working to develop new AI capabilities. Kevin emphasized that this new system will enable more amazing advancements in AI. With GPT-4 and GPT-4 Turbo now available, Microsoft’s CTO stated they have developed an even larger system than the one used for GPT-4. This means we will likely see more advanced AI models soon.

While those are some broad insights about the three major companies, more detailed information might be discussed further.

Alibaba

Alibaba has been actively expanding its AI capabilities, making significant strides in various industries. Their large language model series, Tongyi Qianwen or Qwen, is used by over 90,000 corporate clients in China across sectors like consumer electronics, automobiles, and online gaming. Additionally, 2.2 million users access Qwen-driven AI services through DingTalk, Alibaba’s office collaboration platform. They recently introduced Tongyi Qianwen 2.5, which reportedly outperforms GPT-4 in several Chinese-specific capabilities. Alibaba’s AI models are integrated into applications like Xiaomi’s smart assistant and Perfect World Games, demonstrating their versatility and wide-ranging applications. Additionally, Alibaba researchers have developed technology that can animate any image using an audio file, showing their innovative approach to AI (even though it was not traditionally a full-fledged tech service provider).

Nvidia

Nvidia, known for its powerful graphics processing units (GPUs) that excel in AI applications, has become the third-largest company in terms of market value. Their investments in AI go beyond silicon chips. Nvidia has unveiled its latest AI chip, which is capable of performing some tasks 30 times faster than its predecessor.

Here are some key areas where Nvidia is making significant strides in AI:

Nvidia offers a suite of AI software and tools designed to leverage their GPUs for various tasks. This includes frameworks like Nvidia DeepStream for video analytics applications and its Triton Inference Server for deploying trained AI models.

Nvidia DGX Cloud provides access to pre-configured AI infrastructure with powerful GPUs, pre-trained models, and software tools. This allows companies to develop AI applications without managing their hardware. In 2019, Nvidia acquired Mellanox, a leading networking chipmaker. This acquisition allows them to develop high-performance networking solutions specifically optimized for AI workloads, ensuring efficient data movement within data centres for AI training and inference.

Omniverse Cloud is another example of Nvidia’s advancements, combining GPU-accelerated infrastructure with design and simulation software, which is particularly useful for training AI models used in robotics and autonomous vehicles by allowing the creation of synthetic data for training purposes. It’s a virtual simulated world where robots can independently learn to perform complex tasks, potentially shaping the future of robotics.

Nvidia is also innovating in the field of conversational AI with solutions like RTX Custom Chatbot AI, which uses Retrieval-Augmented Generation (RAG) to enhance chatbot performance. Additionally, HOMEE AI, an Nvidia Inception member based in Taiwan, has developed an “AI-as-a-service” spatial planning solution to disrupt the $650 billion global home decor market. They help furniture makers and home designers find new business opportunities in the era of industrial digitalization using Omniverse. Furthermore, ArchiGAN is transforming the AECO (Architecture, Engineering, Construction, and Operations) sector by generating building layouts, partitioning spaces, and furnishing rooms, automating complex design tasks, and streamlining the construction process.

By investing in these areas beyond just chips, Nvidia is creating a comprehensive AI ecosystem that caters to the entire AI development workflow, from hardware to software to cloud services.

Recently, Nvidia CEO Jensen Huang hand-delivered the first DGX H200 AI system in the world, marking a significant milestone in AI technology. As the AI chip war continues, companies like AMD and Intel are also entering the AI space, but Nvidia remains a dominant force with its advancements and investments in AI technology.

Side Note: Taiwan Semiconductor Manufacturing Company (TSMC) plays a crucial role in the AI arms race by providing the advanced chips needed to power AI applications. TSMC’s chips are integral to the functioning of many high-performance computing systems and AI models. Their cutting-edge semiconductor technology supports the computational demands of AI workloads, making TSMC a key player in the global AI ecosystem.

Apple

(I was writing this a few days before WWDC 2024)

While Apple is known for its focus on user privacy, it is also making strides in AI, which we will witness in the coming days.

I eagerly anticipate Apple’s response to the current AI boom, especially as every other tech giant is diving in. Apart from the basic functionalities Apple has introduced so far, such as upgraded Siri, Apple Music algorithms, satellite features, and watch features, I’m waiting for their real jump into AI. Apple has historically focused more on consumer hardware and supporting software. For instance, their recent Apple Vision Pro is somewhat research on AI and AR, although that’s not the typical business other companies do these days.

Since 2015, Apple has been spending about one billion dollars on AI ventures while remaining silent about developments in self-driving technology, voice design, music generation, and image recognition. It’s their usual tactic to introduce existing technologies under the guise of innovation, and Apple has a knack for marketing these innovations effectively. For example, VR and XR technology have been around for a decade, with companies like Facebook (Meta) and others leading the charge long before Apple. However, the Apple Vision Pro garnered significant consumer attention to these innovations.

Apple has recently held discussions and is rumoured to be in active negotiations with OpenAI and Google about integrating their AI technologies. This potential deal could mark a significant shift in the AI industry.

Rumours suggest that in the coming days, Apple also will introduce eye-tracking technology to control iPads and iPhones, similar to the Apple Vision Pro.

According to sources, when Apple Chief Operating Officer Tim Cook and his team take the stage at the Worldwide Developers’ Conference in Cupertino on June 10, one key announcement may be the launch of generative AI across iPhone-specific applications like Siri and iMessage. The true highlight will be how Apple plans to roll these AI features to its massive installed base of 2.2 billion iOS devices. Emphasizing trust with consumers when using AI could help Apple avoid the pitfalls encountered by Google and others who deployed AI haphazardly.

Apple researchers have developed a new AI model that could potentially outperform GPT-4. In a research paper published on March 29, 2024, they introduced an AI system called ReaLM (Reference Resolution as Language Modeling). This system enhances the understanding of user queries by analyzing on-screen content and user activities. Consequently, Siri is expected to become significantly smarter and faster, offering more helpful assistance than ever before.

The study highlights substantial improvements over existing systems, with even the smallest ReaLM model showing a gain of over 5% in handling on-screen references. Compared to GPT-4, Apple’s ReaLM models achieve similar performance with fewer parameters, making them more suitable for on-device use. ReaLM eliminates the need for complex image recognition parameters by converting images into text, resulting in a more compact and efficient model.

Additionally, Apple previously developed MM1, a family of multimodal large language models with up to 30 billion parameters, designed to achieve state-of-the-art performance in pre-training and deliver competitive results after supervised fine-tuning. The company also acquired DarwinAI, a Canadian AI startup, underscoring Apple’s commitment to advancing its AI capabilities.

This being said, Tim Cook, while not traditionally seen as a product genius, has kept investors happy with increased share buybacks despite slowing iPhone and Mac sales. Apple must find its next big thing, and AI could be a significant part of that future. According to sources, Apple is also exploring the creation of home robots as their next big venture, highlighting their commitment to integrating AI into innovative consumer products.

Update: Post-WWDC 2024

In my opinion, Apple typically introduces its products and services with some AI features without explicitly labelling them as such or providing detailed statistics on their performance. However, in response to the rise of generative AI, Apple announced “Apple Intelligence” During WWDC 2024. This new system allows Siri to understand icons, widgets, and text on a screen and take action via the apps’ own AI systems. Apple Intelligence will power various AI features across iPhones, iPads, and Macs. Focused on privacy, Apple Intelligence uses on-device processing or Apple’s private cloud servers to fulfil user requests. Siri enhancements include deeper AI integration, enabling it to better understand the context and surface information within apps and even control certain device functions. Apple is also infusing its native apps with AI capabilities. For example, Mail now includes AI-powered summaries, Messages introduces a new Genmoji feature, and Photos offers AI image generation.

Regarding the rumours and leaks mentioned before, Apple is integrating ChatGPT into Siri, allowing users to leverage GPT-4o capabilities through voice commands. SVP Craig Federighi confirmed plans to work with additional third-party models, saying, “We’re looking forward to doing integrations with other models, including Google Gemini, for instance, in the future.” Although OpenAI’s ChatGPT will be the first third-party model to receive integration later this year, Apple users can access the system without signing up for an account or paying for premium services. This partnership suggests that Apple is covering up the fact that they do not have an in-house AI model without stats and have marketed AI as “Apple Intelligence” just to dive into the business.

Hilariously, Elon Musk (you know, he always comments out something) voiced privacy concerns about Apple’s new AI plans. In a post to X, Musk threatened to ban Apple devices from his companies, including SpaceX and X, if Apple integrates OpenAI at the operating system level, calling it “an unacceptable security violation.”

He suggested that visitors would have to check their Apple devices into a Faraday cage, blocking all communications. Musk claimed, “Apple has no clue what’s going on once they hand your data over to OpenAI,” accusing them of selling out user privacy.

Musk’s remarks came shortly after Apple announced their partnership with OpenAI at the Worldwide Developers Conference, aiming to integrate generative AI tools into their products. Although, I must admit to Musk’s concerns regarding privacy.

Samsung

With that being said, nevertheless, people still glorify the fact that whatever Apple makes is a big deal, and that’s the news across all media platforms. It’s crazy because, as someone who follows many tech fields, I see numerous innovations happening daily. Yet, Apple’s marketing prowess overshadows even major players who can’t compete on that front. For instance, look at how Samsung introduced its AI.

Samsung recently unveiled its “AI for All” vision, which focuses on home automation, health, and mobile experiences:

Samsung’s SmartThings platform can now create digital floor plans and detect unusual circumstances like falls, sending alerts to designated family members. The platform uses smart sensors and AI to manage home devices efficiently. AI powers feature in Samsung Health, offering personalized health insights and seamless device integration. New products like the Galaxy Ring and enhanced capabilities on Galaxy Watch 6 provide comprehensive wellness tracking. The Galaxy S24 series includes features like Live Translate for real-time language translation and advanced camera functionalities with the ProVisual Engine. Additionally, ensuring more secure operations with on-device processing, protecting user data from external threats. (Gosh, aren’t these like super old news in the current AI landscape?)

Amazon

Amazon has been a significant player in the AI industry, leveraging its technology across various products and services. The company’s AI capabilities are prominently showcased in its cloud computing platform, Amazon Web Services (AWS), which provides a suite of AI and machine learning services. Amazon’s AI is integrated into many of its consumer products, such as the voice-activated assistant Alexa, which uses natural language processing to interact with users.

Amazon has introduced its Large Language Model (LLM) named Olympus. This model is designed to enhance the capabilities of various AI-driven applications within Amazon’s ecosystem. Olympus is utilized to improve recommendations, streamline logistics, enhance search functionalities, and optimize overall customer experience across Amazon’s services.

Recently, Amazon has focused on making Alexa smarter and more conversational. They have been previewing a new generative AI model specifically optimized for voice interactions, aimed at making Alexa as natural to converse with as a human. This involves using advanced AI to understand non-verbal cues, reduce response latency, and perform real-world tasks more effectively. For example, Alexa can now set up complex routines entirely by voice, seamlessly managing various smart home devices.

In terms of cloud computing, AWS continues to be a major benefactor of AI workloads, providing the infrastructure necessary for training and deploying AI models. This includes support for a wide range of applications, from data analytics to machine learning. AWS has also become increasingly popular in AI due to its robust and scalable cloud services.

Amazon is also investing heavily in generative AI startups, with plans to spend $230 million to enhance its AI capabilities further. This move aligns with their broader strategy of integrating AI across all their services to stay competitive in the evolving tech landscape.

Additionally, Amazon faces challenges and criticisms regarding its use of AI in customer service, including layoffs and concerns about abusive calls. These issues highlight the complexities and risks associated with deploying AI at scale in real-world applications.

By integrating these advancements and addressing challenges, Amazon aims to maintain its position as a leading innovator in the AI industry, continually enhancing its products and services to meet the needs of its vast user base.

IBM

IBM has long been a pioneer in the field of AI, with a strong focus on AI for business applications. The company’s AI platform, Watson, is renowned for its natural language processing, data analytics, and machine learning capabilities. IBM Watson is utilized across various industries, including healthcare, finance, and customer service, to drive innovation and improve operational efficiencies. IBM continues to invest heavily in AI research and development, aiming to push the boundaries of what AI can achieve in the business world.

However, it’s important to note that IBM is more of a development and research company rather than a direct provider of consumer products. The reason for mentioning IBM here is to acknowledge its significant contributions to all sides of IT, not to extend the article unnecessarily. IBM’s advancements have had a profound impact on the technology landscape, making it a crucial player in the ongoing development of AI. IBM helps set industry standards and drive technological progress, benefiting various sectors. Their contributions to the AI field are a testament to their commitment to innovation and excellence in technology (Too much boasting, I know).

Twitter (now known as X)

In the realm of social media, Twitter, which has rebranded itself as X, has introduced its AI model Grok-1. This model is aimed at improving content moderation, enhancing user engagement, and providing better insights into user behaviour. Grok-1 leverages advanced machine learning techniques to analyze vast amounts of data generated on the platform, helping to create a safer and more engaging environment for users.

Elon Musk also plans to start his own AI empire with his AI startup, X AI, which has raised six billion dollars from Valor, A16Z, G, and Sequoia.

Recently, Meta’s AI chief, Yann LeCun, mocked Elon Musk on his own platform, X, following Musk’s attempts to recruit AI workers for his company X AI. LeCun criticized Musk’s claims and behaviour, including his prediction that AGI will be solved next year and his controversial statements about the potential dangers of AI. The ongoing feud between the two tech rivals dates back to at least 2017. Yann LeCun, one of the three AI godfathers, is famous for his early research that laid the groundwork for today’s AI, including his work on convolutional neural networks (CNNs), which revolutionized the field of computer vision and enabled significant advancements in tasks such as object detection.

This is not an exhaustive list, but it gives you a good overview and comprehensive detail of some of the major players in the AI space. The field constantly evolves, so it’s worth watching new developments and emerging companies. Many other companies are coming into play, and we will see them shortly somewhere in the article. Big money follows good ideas, not just the inventions themselves.

Large language models, like ChatGPT, have the potential to be revolutionary. However, the companies that truly profit will be the ones that use this technology in unique ways. The key to success in business lies in finding that special something to set the company apart.

Understandably, these major corporations are in desperate competition for leadership, in one form or another, in developing and deploying AI. It seems it’s a collaborative effort with all these companies, while there’s a big competition and business.

All the companies mentioned have been contributing to AI in some way for a long time, but they started marketing these advancements more aggressively after the recent AI boom. I may have missed some major developments or overlooked key players, but these highlights provide a snapshot of the current landscape. While this list includes some of the prominent names, there are certainly more contributors in the AI field worth noting.

Alright, let’s dive into some cool and more advanced topics on AI that are yet to come

AI in Robotics

Speaking about robotics, NVIDIA CEO Jensen Huang says robots will be the next wave of AI.

“The next wave of AI is physical AI. AI that understands the laws of physics. AI that can work among us. Everything is going to be robotic. All of the factories will be robotic. The factories will orchestrate robots, and those robots will be building robotic products.”

Soon, humanoid robots might be available for $10,000 to $20,000. Huang mentioned the potential of humanoid robots in our daily lives, with the Ameca robot being a notable example.

OpenAI also introduced Figure 1, a robot capable of full conversation with AI humans to perform tasks simultaneously. Figure, an AI robotics company worth $2.6 billion, partnered with OpenAI to develop Figure 01, marking the first time both companies worked together. With OpenAI, Figure 1 can now have all conversations with people.

Boston Dynamics has revealed their next-generation humanoid robot designed for real-world applications. The new Atlas, built on decades of research, furthers their commitment to delivering the most capable and useful mobile robots, solving the toughest challenges in the industry today. However, Boston Dynamics has retired their humanoid robot HD Atlas, which didn’t always have the easiest times.

Furthermore, a team applied technologies to quickly and accurately position bias in motors for electric appliances such as air conditioners and ventilator fans. This technology enabled a Japanese robot to rotate one of a Rubik’s cube’s 6 phases by 90 degrees in a record time of 0.305 seconds. The colours of individual panels were recognized by cameras using AI technologies. Although the robot failed to solve the puzzle on its first attempt, and the team spent about 20 minutes adjusting the machine, it now holds a world record.

It’s been a while since the military and army have worked with robotics innovations for their safety and future ammunition. The Chinese army has been seen with a robot dog equipped with a machine gun, which is quite alarming.

Throwflame introduced the first-ever flame-throwing contraption, a robot dog capable of shooting fire up to 10 meters.

The advancements are getting out of hand, with Microsoft and OpenAI’s hundred-billion-dollar AI supercomputer, StarGate, set to be powered by several nuclear power plants.

Chinese robotics technology firm LimX Dynamics’ Biped Robot P1 demonstrated the machine’s ability to respond remarkably well when threatened by a human. According to the firm, the robot uses reinforcement learning to respond to outside stimuli, such as moving objects or bumps on a path. Reinforcement learning is a subset of techniques used to train AI algorithms, and this news builds on Zhuji Dynamics’ steady development of robotic technologies.

There are advancements in robotics, starting from basic robots using high precision to peel an egg, puncture it, and stitch it back using computer vision. Additionally, a new AI robot, which is more like a fish, autonomously explores underwater. A Ukrainian company developed an AI-controlled turret for trench defence. High-speed AI drones beat world champion racers for the first time. Other robotics innovations include Tesla’s new Gen 2 Optimus bot, which learns by watching humans.

Scientists have created an AI replica of a baby that can grow and learn over time. Amazon deployed over 750,000 robots in 2023 to unlock AI opportunities. Disney’s robot with human-like facial movements is both impressive and horrifying. Some South Asian robotic firms are trying to make durable robots with walking and balancing capabilities. In China, they’ve already achieved Westworld season one-level robotics with their humanitarian robots.

Google’s DeepMind also creates robots trained in simulation through deep reinforcement learning, which can now play 1V1 games. Disney researchers showcased cute AI-powered Star Wars robots during Nvidia’s GTC 2024. Nvidia announced Project GR00TA, a foundation model for human and robot learning and simulation in the real world.

Bionic limbs powered by AI are revolutionizing the lives of amputees by providing more natural and intuitive control. Researchers at the BLINC Lab (Bionic Limbs for Improved Natural Control) use reinforcement learning to create “smart” prosthetics to predict a person’s movements, allowing for smoother and more responsive operation.

In a groundbreaking development, the world’s most advanced robotic massage has been introduced in New York City. Utilizing sophisticated AI and robotic technology, this massage provides precise, customizable treatments that cater to individual needs. (Guys, Terminator is coming lol)

The Current Landscape of Humanoid Robots

AI in Automobile

Automobile giants are also moving into AI hybrid technologies, such as self-driving cars, which come to mind when discussing this topic. Speaking of self-driving cars, Tesla often comes to mind. Recently, Tesla’s full self-driving system perfectly handled an unprotected left turn at a chaotic intersection, demonstrating the advancements in autonomous vehicle technology.

Furthermore, with AI-powered advancements, Samsung is set to revolutionize the driving experience in the automobile sector. The partnership with Hyundai allows SmartThings to connect seamlessly with Hyundai, Kia, and Genesis vehicles, facilitating functionalities such as remote climate control and window operations through voice commands. This integration extends to home automation, where users can directly manage home functions like garage doors and temperature settings from their vehicles. In collaboration with HARMAN, Samsung is also enhancing in-cabin experiences with technologies like Ready Care, which uses deep learning to monitor driver alertness and provide personalized safety alerts, and Ready Vision, which offers augmented reality displays on windshields for real-time navigation and recommendations.

A recent video showed Nissan’s self-parking AI office chairs designed for their offices. Additionally, someone explained how WiFi routers could change into cameras and track people through walls using AI. In China, AI is being used to monitor employee productivity, sounding an alarm if someone isn’t working or leaves their desk. A recent short film exposed the dark side of sharing everything online with the help of AI.

Recently, Researchers from the University of Tokyo published a study exploring a new approach to autonomous driving (Instead of automating the entire car, simply put a robot in the driver’s seat).

AI in Medical and Healthcare

Let’s dive into some advanced AI topics in the realm of medical and healthcare advancements:

Bainbridge is a company that claims to be developing a head transplant system using advanced robotics and AI, representing a landmark achievement in neuroscience and human engineering. However, this company doesn’t exist; the claim was part of a viral video created by a communications professional.

Anthropic, founded by former OpenAI executives and researchers, has made its AI assistant, Claude, available in Europe. The company focuses on AI safety research, with Google and Amazon as major investors.

At Vidu AI, the company leverages deep learning to solve some of the world’s most puzzling problems in medicine, healthcare, and life science research.

Researchers have used AI to reveal distinct cellular-level differences in the brains of men and women, focusing on white matter. These findings show that AI can accurately identify sex-based brain patterns invisible to human eyes. Understanding these differences can enhance diagnostic tools and treatments for brain disorders, emphasizing the need for diversity in brain studies to ensure comprehensive insights into neurological diseases.

AI has successfully changed human DNA using gene editing. Profluent has trained an LLM on a massive amount of biological data, enabling the model to generate millions of diverse CRISPR-like proteins that don’t exist in nature. They aim to produce gene editors more efficient and capable than existing biological mechanisms, allowing organisms to ward off diseases. They are open-sourcing this editor, hoping to leverage other researchers’ expertise to improve the model over time. Additionally, AI can now decode human thoughts and reconstruct what we’re looking at based on our brain patterns.

Neuralink is a neurotechnology company that develops advanced brain-computer interfaces (BCIs). The integration of AI is essential to Neuralink’s mission, enabling the decoding of neural signals, recognition of patterns, and real-time interaction between the brain and external devices. This technology holds promise for treating neurological disorders, enhancing human capabilities, and opening new frontiers in human-computer interaction.

Neuralink recently made headlines by implanting its first brain chip in a human patient as part of its PRIME study. The goal is to help people with severe physical disabilities control external devices using their thoughts. However, the implant faced challenges when some ultra-thin threads retracted from the patient’s brain, reducing functionality. Neuralink engineers addressed these issues by refining the recording algorithms, improving the user interface, and restoring the device’s performance. Despite these initial setbacks, the patient could use the implant to perform tasks such as playing chess and controlling a computer cursor with thoughts. However, the company faced significant challenges, which led to an unsuccessful outcome in its initial phase. The retracted threads decreased the number of effective electrodes, reducing the device’s capability to transmit neural signals accurately. The brainship implant malfunctioned, and the company reportedly removed it from the human patient.

Several companies are advancing BCI technology alongside Neuralink:

Synchron: Developed the Stentrode, a minimally invasive BCI inserted via blood vessels, allowing paralyzed patients to control tablets and smartphones without open brain surgery. It received FDA Breakthrough Device Designation in 2021.
Precision Neuroscience: Founded by a former Neuralink executive, it uses a flexible electrode array implanted through a small incision, avoiding open brain surgery. Human trials began in 2023.
Paradromics: Focuses on a high-bandwidth interface with a chip connected to a wireless transmitter in the chest, promising significant data transmission capabilities.
Blackrock Neurotech: Uses the Utah Array, a high-density electrode array used in academic research. Their MoveAgain device received FDA Breakthrough Designation in 2021.

Google recently released Gemini for medical tasks, outperforming GPT-4 by 44.5%. It excels in tasks like medical summarization, generating doctor’s notes, and simplifying medical documents, proving more effective than human experts for complex medical tasks. This new model surpasses GPT-4 across various medical benchmarks, achieving an impressive 91% accuracy, indicating a huge advancement in AI for healthcare. Scientists have successfully implanted a brain-computer interface (BCI) in a rat’s brain, achieving stunning accuracy in predicting neural activity and merging biomechanics with AI.

This is just a glimpse into the exciting and rapidly evolving field of AI in robotics, defence, automobile, healthcare, and more, highlighting the potential for significant impacts on human-computer interaction.

AI in Outer Space and Networking Technology

If we take outer space and networking technology, companies like Starlink, Qualcomm, OneWeb, and Globalstar are making significant advancements with AI.

Starlink, the satellite internet constellation project developed by SpaceX, uses AI to optimize satellite positioning, dynamic routing, and predictive maintenance to ensure efficient global internet connectivity.
Qualcomm integrates AI into its 5G technology and edge computing solutions to enhance network performance and connectivity. They are also collaborating with Ampere on AI initiatives.
OneWeb leverages AI to manage its satellite network for consistent global internet service.
Globalstar collaborates with Qualcomm to incorporate AI in their 5G private networks, optimizing data handling and performance.

Additionally, Jio has started integrating AI with its Jio Brain project, aiming to enhance its telecom services and infrastructure. These companies are pushing the boundaries of what’s possible with AI in their respective fields.

In the aviation industry, airlines are exploring the use of AI to predict where turbulence might occur. This application of AI could significantly improve flight safety and passenger comfort by allowing pilots to avoid turbulent areas and provide smoother flights.

AI in Software Development

In the realm of software development, AI is making significant strides, not only from a consumer perspective but also from the viewpoint of the developers and creators who are leveraging these advancements.

GitHub Copilot: GitHub Copilot, developed by GitHub in collaboration with OpenAI, is an AI-powered code completion tool. It assists developers by suggesting code snippets, generating entire functions, and even completing lines of code, thereby boosting productivity and reducing repetitive tasks.
Postman Chatbot: Postman, a popular API development tool, has integrated AI to enhance its chatbot capabilities, aiding developers in creating, testing, and managing APIs more efficiently.
Devin AI: Cognition AI Inc. introduced Devin AI as the world’s first AI software engineer. Devin AI is designed to assist users with coding and machine learning tasks, potentially replacing junior full-stack engineers. Despite its groundbreaking potential, the tool faced challenges and did not achieve the expected success due to several mistakes and timing issues.

In response to Devin AI, an Indian company introduced Devika AI, an open-source AI software engineer crafted by Stition AI. These tools interpret complex human instructions, break them into manageable tasks, conduct thorough research, and write code to achieve specific goals. This sophisticated AI system aims to democratize intelligent software development tools and is seen as a formidable rival to Devin AI.

The development of AI software engineers has not been entirely smooth. For instance, Devin AI faced significant setbacks and was ultimately deemed unsuccessful, leading to the sarcastic comment “Devin Weds Devika”, which humorously captured the challenges and competition in the field.

Introducing AI tools like AI Copilots and Dein AI represents a new era in software engineering. These tools can potentially revolutionize the industry by offering cost-effective solutions and increasing efficiency. However, the journey has not been without its challenges, as seen in the case of Devin AI.

As AI continues to evolve, it’s crucial for software developers to stay ahead by learning the core principles of AI and machine learning, not just how to use AI tools and Continuous Learning.

As I saw a meme that says:

“I learn from the mistakes of people who took my advice.” — ChatGPT

This humorous insight underscores the importance of learning from mistakes, whether yours or those of others. In programming, every bug is just a feature waiting to be discovered, and understanding AI’s dependence on accurate data and algorithms is key to leveraging its full potential.

While much of the focus on AI advancements centres on Western tech giants, significant breakthroughs are also happening in Asia and other parts of the world. Here are some noteworthy examples:

China’s Sensinova 5.0 AI model has reportedly outperformed OpenAI’s GPT-4 Turbo in various benchmarks, demonstrating the rapid advancements and competitive edge of Chinese AI technology. This model excels in natural language processing tasks and showcases the potential of China’s AI research and development.

China’s Kuaishou released a Sora competitor called Kling, a new text-to-video Al model that can generate 120s videos with 30FPS at 1080p and is now available in China.

Other Notable AI Innovations

Reka AI is an emerging company making significant strides in AI research. They focus on developing innovative AI models and applications, particularly in the fields of machine learning and data analytics. Their contributions are shaping the future of AI with unique and practical solutions.

Snowflake is known primarily for its cloud-based data warehousing services. Snowflake is also making inroads into AI and machine learning. They provide robust platforms that enable data scientists and developers to build and deploy AI models efficiently. Snowflake’s integration of AI capabilities enhances data processing and analytics, offering comprehensive solutions for businesses.

Unbabel leverages AI to provide translation services, combining the efficiency of AI with the quality of human translation. Their AI model excels in language processing, offering accurate and contextually relevant translations. This technology is particularly valuable for global businesses looking to bridge language barriers and enhance communication.

Luma AI recently launched Dream Machine, a new generative AI platform designed to create high-quality videos from text prompts. Dream Machine has been positioned as a competitor to OpenAI’s Sora, with some key advantages.

Dio just dropped Audio Prompting, and it’s unprecedented. People can “Upload” their music/sound, and the Al will extend it with sounds and lyrics.

Let’s move to the final stage of this article

First of all, I should agree that the majority of AI consumers don’t know which apps exist beyond the popular ones like ChatGPT and Gemini. However, there are many other innovative AI tools available. For example, Midjourney, DALL-E, Descript AI, Compose AI, Bardeen, Black Box AI, Perplexity AI, and numerous other services have been introduced.

As discussed earlier, Generative AI has become a crucial part of our lives, impacting fields such as research, text, video, image, code, speech, and 3D modelling. Many applications and integrated tools have emerged, particularly with the advancements of OpenAI’s GPT, Google’s Gemini, and Meta’s LLaMA models.

While many new applications are being developed and released, numerous alternatives are already available for users. Moreover, tons of custom APIs and third-party plugins powered by GPT are available, like Slack and FigGPT, etc. These AI-powered tools are rapidly becoming indispensable in various domains. Therefore, for an extensive list of AI services, you can visit There’s an AI for That, which provides instant information about the latest AI tools and services.

Exploring Other AI Tools

Now, numerous applications are available for generating web applications, resumes, text-to-image generation, and audio enhancement. Speaking of a random finding, there’s an application called DragGAN, which is similar to Midjourney. It allows users to easily manipulate images. Another impressive application can instantly fix old retro photos, showcasing the array of cool and easy AI applications available right now.

Furthermore, AI chatbots are replacing traditional search methods. Search engines are evolving, with Google integrating AI into Chrome browsers and Bing Chat being replaced by Microsoft Copilot. Both Microsoft and Google are incorporating AI into their ecosystems to improve user experiences.

Speaking of Canva, it has announced impressive AI features. Initially, Canva introduced chat-like AI features, but now it includes video editing, photo editing, and many other advanced features expected from AI.

AI in Hollywood

Hollywood is another industry being disrupted by AI. Filmmaking will soon change entirely due to AI. AI-generated short films and movie trailers are emerging, and many VFX artists are being replaced by AI technology. AI in filmmaking is inevitable. As George Lucas once said, “I don’t believe these cars are gonna work; let’s just stick with the horses.” Sam Altman also commented that movies will become video games, and video games will become something unimaginably better. However, many companies withhold significant AI technologies from the public due to safety concerns, like OpenAI, which has tech that can clone someone’s voice in 15 seconds but hasn’t released it publicly.

In the video gaming industry, we will see wholly AI-generated games in five to ten years, as Jensen Huang mentioned. AI is also revolutionizing audio engineering, bringing us closer to perfect sound experiences.

AI in Travel and Tourism

AI is also making strides in travel and tourism. For example, some technologies animate paintings with AI at the Dubai Art Museum, bringing art to life. We might see more innovative uses of computer vision, such as requiring users to do 20 pushups to unlock more screen time on social media and blending health and technology seamlessly.

Beyond the consumer market, where the general public enjoys many AI-driven services and products, numerous research programs and innovators are developing groundbreaking AI applications. Young students and hobbyists are at the forefront, creating impressive projects such as sign language translators and accurate aiming bots using Python (Yes, these are the “way old” facts). This grassroots innovation is paving the way for a promising future, demonstrating the incredible potential of AI when driven by creativity and passion.

AI is also making significant strides in various unexpected domains. In education technology, AI-driven platforms are transforming personalized learning and administrative efficiency. For instance, tools like Coursera and Khan Academy utilize algorithms to tailor educational content to individual student needs (I have even done a project on that). AI’s impact on environmental sustainability includes advancements in climate modelling, energy-efficient technologies, and wildlife conservation efforts. For example, Google’s DeepMind has successfully applied AI to enhance the energy efficiency of its data centres. In cybersecurity, AI plays a crucial role in threat detection, prevention, and response, enhancing the capabilities of security systems to protect against increasingly sophisticated cyber threats. These diverse applications highlight AI’s potential to revolutionize various fields beyond the conventional tech landscape.

With a high degree of scientific certainty, we can say that GPT-5 will be significantly smarter than GPT-4, and GPT-6 will surpass GPT-5. We are not near the top of this curve, and the potential for AI advancements is immense.

Elon Musk predicted that AI would probably be smarter than any human by next year, and by 2029, AI would be smarter than all humans combined. Looking ahead, it’s not far-fetched to imagine that in the near future, you can translate what your cat or dog is saying to you (There should be an AI for that).

The future of AI promises transformative changes by integrating various advanced technologies. Current innovations, however, are still limited and not fully sophisticated. Combining generative AI, humanoid concepts, advanced networking, and several other features could create a powerful supercomputer that functions as both a robot and a versatile computing device, potentially replacing many current devices. This vision reflects a trajectory where AI evolves beyond its current applications, paving the way for unprecedented advancements.

Despite significant progress, the development of AI is facing challenges and limitations. For instance, Sam Altman of OpenAI mentioned that GPT-4 might be the “dumbest generative AI language model” we will use, indicating that much more advanced models are yet to come. This sentiment aligns with the broader observation that while current AI technologies are impressive, they are far from reaching their full potential.

Integrating AI’s future potential, like cognitive advancements, could revolutionize our interaction with digital devices, creating a seamless interface between humans and machines.

Historically, advancements in computing have faced physical limitations. For example, the expected exponential growth in CPU speeds hit a plateau due to power and heat constraints, leading to a focus on efficiency and parallel processing rather than raw speed increases. Similarly, AI development might face diminishing returns if it relies solely on scaling existing models without architectural innovations. This is evident in the current plateau of scaling large language models like GPT-4, which require massive computational resources for marginal performance gains.

Some experts believe AI is currently overhyped, with businesses capitalizing on the buzz to drive profits rather than genuine advancements. However, the integration of AI with other technologies holds significant promise.

While current AI technologies are remarkable, they represent only the beginning of what is possible. Future advancements will likely come from combining AI with other cutting-edge technologies, leading to innovations that surpass today’s capabilities and transform our digital landscape. However, achieving this future will require overcoming current limitations and moving beyond the hype to realize AI’s true potential.

Former OpenAL researcher Leopold Aschenbrenner says, “AGI by 2027 is strikingly plausible. That doesn’t require believing in sci-fi; it just requires believing in straight lines on a graph.”

Artificial General Intelligence (AGI) is an AI that can understand, learn, and apply knowledge across various tasks, potentially surpassing human intelligence. Sam Altman of OpenAI has stated, “I don’t care if we burn $500 million or $50 billion, we’re making AGI, and it’s gonna be worth it.” He suggests that in the short term, things change less than we think, but in the long term, things will change more than we think. Altman believes GPT-5 will be significantly smarter than GPT-4 and that global access to computers is a human right, with a mission to figure out how to distribute that access.

Looking ahead, the concept of supercomputers more powerful than humanoid robots is becoming a reality. These advanced systems will integrate all current AI features, transforming them from prototypes into fully operational tools. In the future, AI will be seamlessly integrated into everyday applications. For instance, search engines and virtual assistants like Google Assistant and Siri will evolve into specialized forms, incorporating advanced AI capabilities directly into their services. This integration means users will no longer need to access separate AI platforms like ChatGPT or Gemini, as these functionalities will be embedded in their daily digital interactions.

Despite having all these innovations, some experts fear AI could be used for malicious purposes. These programs sometimes generate inaccurate answers and images and can reproduce biases contained in their source material, such as sexism or racism.

Deepfake technologies are particularly dangerous and concerning. Meta has addressed this by labelling deep fakes as “made with AI” and providing context about the manipulated media.

While there are many concerns around AI, its impact on socialization is another major issue. Many lonely teens are making friends with AI. High schoolers feeling isolated are now using AI chatbots not only for academic assistance but also for companionship and emotional support. These teens find chatbots more interactive than traditional journaling, serving as a pseudo-therapeutic outlet without the fear of judgment. These platforms have seen over 113 million interactions, indicating their widespread acceptance.

Teens often use these services for candid discussions about personal issues, appreciating the anonymity and lack of judgment. Users engage with various chatbot personas ranging from fictional characters to historical figures, with some specifically designed for romantic or even sexual interaction. The average user spends about two hours daily engaging with these chatbots, with some reporting over 12 hours of interaction.

Despite potential concerns about addiction, many users report that these interactions help them develop better social skills, providing a safer space to practice interpersonal interactions. For some, communicating with AI is more comfortable than face-to-face interactions. Nowadays, there are so many AI bots specifically designed to be customized in various ways, allowing users to create their ideal conversational partner (Hmmh).

There are growing concerns about AI-generated content contributing to brain rot and its impact on adult entertainment.

In another development, as you all may know, Google has stopped image generation temporarily due to inaccuracy, addressing concerns about the potential harm caused by AI-generated content.

Tech companies have agreed to an AI kill switch to prevent Terminator-style risks. What I am trying to say here is tech companies and governments are working together to manage AI risks, including a voluntary kill-switch policy to halt advanced AI development if risks surpass certain thresholds. This policy, however, lacks legal enforcement and specific definitions of these thresholds.

At a recent summit in Seoul, 16 major AI companies, including Anthropic, Microsoft, and OpenAI, agreed to this policy. A similar meeting at Bletchley Park followed this summit, criticized for lacking actionable commitments. Experts have long warned about AI risks, notably the Terminator scenario where AI could turn against humans.

AI leaders acknowledge both the opportunities and dangers of advanced AI. OpenAI CEO Sam Altman has mentioned the risks of AI, including AI and AGI. Efforts to regulate AI globally have been fragmented and mostly non-binding. For example, a recent UN policy framework is non-binding. However, some governments, like the US and China, have enacted formal AI policies to address these concerns.

To avoid the problem of AI producing harmful content, scientists have created a toxic AI that is rewarded for thinking of the worst possible questions we could imagine. AI checkpoints have had unprecedented success in answering questions and providing virtual assistance, but scientists are concerned about the potential for large language models to provide users with misinformation and hateful and harmful content.

For example, while GPT could successfully write a computer program, it also has the potential to provide instructions on how to make a bomb if requested, according to researchers at MIT. To combat these potentially problematic chatbots, they have developed a solution using another AI that is also dangerous and toxic.

It may sound bizarre at first, but the idea uses a method that replicates human curiosity to get the AI to provide increasingly dangerous responses to disturbing prompts. These responses are then used to identify how to filter potentially harmful content and replace it with safe answers.

There are significant drawbacks and negative impacts associated with AI contributors themselves. Companies that develop AI technologies are experiencing internal upheavals, with notable figures like OpenAI’s co-founder leaving and rejoining the company. This trend highlights the volatility within the industry.

In a surprising move, OpenAI’s co-founder and chief scientist, Ilya Sutskever, known for questioning Sam Altman’s ambition to deploy AI quickly, announced he was leaving the start-up. This decision follows a tumultuous period within the company, including the firing and subsequent rehiring of CEO Sam Altman and President Greg Brockman, in which Sutskever was initially involved. The internal conflicts and differing views on the pace of AI development led to significant changes in the company’s leadership structure. Sutskever expressed confidence in OpenAI’s future under the current leadership and mentioned that he is moving on to a new project that is personally meaningful to him (I generated this since I was lazy to read their drama, so-called publicity stunts)

Current and former OpenAI employees and other AI researchers are willing to reveal confidential secrets to the public. They have released an open letter entitled ‘A Right to Warn about Advanced Artificial Intelligence’.

One of the other major concerns is privacy. The vast amount of data collected to improve AI raises questions about data security and user privacy. Due to the growing data needs in AI, web scraping has become more common. Web scraping involves extracting data from websites, and it’s legal if you’re accessing publicly available information. Integrating AI into systems that monitor every user’s action could essentially turn these systems into sophisticated spyware, leading to increased concerns about privacy infringement and data misuse.

Let’s talk about inaccuracies (well, machines make mistakes). Google has already started integrating AI into its search engine, but the results have been mixed. There have been instances of AI generating bizarre and inaccurate responses, such as advising that smoking while pregnant is acceptable as long as it’s non-toxic. These odd answers highlight the need for continuous improvement and monitoring of AI systems to ensure they provide reliable and accurate information.

A faculty of facial recognition AI led to the wrongful arrest of a black woman in Detroit last summer after police used a program that identified her as the suspect based on an old mug shot. The case was later dismissed, but Porsche Woodruff’s arrest remains on the public record of the 36th District Court of Michigan.

A 2018 study found that darker-skinned women were most likely to be misidentified by facial recognition technology, with an error rate of 35%. Six years later, AI is still making troubling mistakes, including misidentifying darker-skinned people and showing biases when faced with language associated with non-white speakers.

Well, last but not least, the trending topic (Job replacements).

As most of us might have seen, an advertisement by 5 Star Chocolate humorously predicted a future where AI takes over many jobs, creating a “nothing university” to highlight a world where people do nothing because AI handles everything.

Elon Musk recalculated his cost-benefit analysis of AI risks to humankind, estimating that there is a 10 to 20% chance AI could destroy humanity, but he believes we should build it anyway. An AI safety expert told Business Insider that Musk is underestimating the risk of potential catastrophe.

The computer scientist regarded as the “godfather of artificial intelligence,” Professor Geoffrey Hinton, has stated that the government will need to establish a universal basic income to address the impact of AI on inequality. He told BBC Newsnight that a benefits reform, giving fixed amounts of cash to every citizen, would be necessary because he is “very worried about AI taking lots of mundane jobs.” Hinton advised Downing Street that universal basic income is a good idea, as AI will increase productivity and wealth, but the money will likely go to the rich, not to those whose jobs are lost, which could be detrimental to society.

With 71% of leaders favouring less experienced candidates with AI skills over more experienced ones without them, professionals are urged to adopt and master AI tools.

A Financial Times report mentioned that over 600,000 employees worldwide expressed concerns that AI would lead to a minimal need for call centres. The CEO noted that while no significant job reductions have occurred, this will change as multinational clients adopt the technology. The customer help centre industry is expected to experience a massive transformation due to AI.

In my opinion, Generative AI will likely create more job opportunities than there are people to fill them, creating a paradox of job abundance. Concerns about widespread job replacement due to AI are unlikely to materialize in the near future. While generative AI could significantly impact industries such as call centres, it’s expected that it will not replace jobs outright but rather change how they are performed.

The notion that “AI won’t replace jobs, but the person using AI will” reflects the idea that those who leverage AI effectively will have a competitive advantage. For instance, a person using AI to solve problems may not need to hire additional help, and conversely, someone who uses AI without applying their knowledge may become obsolete.

Automation is increasingly replacing jobs, with an ABBC report suggesting that AI could replace the equivalent of 300 million full-time jobs. Instead of fearing AI, there are ways to take advantage of it. Building a following and engaging authentically with an audience can be a valuable strategy for leveraging AI to create income opportunities. Moreover, GPT-4 has demonstrated remarkable capabilities in the financial sector. A report highlighted that GPT-4 can predict earnings more accurately than human analysts on Wall Street.

Elon Musk recently commented that AI could take away not only jobs but also the meaning of life, highlighting the profound impact AI could have. Google and Microsoft are laying off hundreds from their cloud units as they focus on AI advancements.

Sam Altman of OpenAI emphasized that critical thinking, creativity, and the ability to understand what others don’t will be the most valuable skills in the future. To future-proof your career in the AI age, it’s essential to develop these skills.

This article should serve as a comprehensive keyword search for Artificial Intelligence, offering an extensive overview of its transformative impact across various industries. From major players like Apple, Google, OpenAI, and Microsoft to emerging technologies and applications, you’ll find a wealth of information on how AI shapes our world. Follow the links provided throughout the article for detailed explanations and technical terms. Dive deeper into the innovations, challenges, and potential of AI to fully understand its evolving landscape and the implications for our future.

While this article focuses on major players in the AI field, it’s crucial to stay updated with the latest developments. I may update this piece occasionally as new updates emerge, aiming to reflect the user’s perspective while acknowledging some inherent bias. A big shoutout goes to other news sources that provided valuable content and insights for this article. I may not have given credits clearly, but I acknowledge their contributions.

Source link

Source link: https://aamilaliyar.medium.com/beyond-the-hype-a-deep-dive-into-the-past-present-and-future-of-ai-8dc5ce041177?source=rss——large_language_models-5