The bubble that thinks: Sam Altman’s AI paradox

AI Bubble?

Sam Altman, CEO of OpenAI, has never been shy about bold predictions. But his latest remarks strike a curious chord reportedly saying: ‘Yes, we’re in an AI bubble’.

‘And yes, AI is the most important thing to happen in a very long time’. It’s a paradox that feels almost ‘Altmanesque’—equal parts caution and conviction, like a person warning of a storm while building a lighthouse.

Altman’s reported bubble talk isn’t just market-speak. It’s a philosophical hedge against the frothy exuberance that’s gripped Silicon Valley and Wall Street alike.

With AI valuations soaring past dot-com levels, and retail investors piling into AI-branded crypto tokens and meme stocks, the signs of speculative mania are hard to ignore.

Even ChatGPT, OpenAI’s flagship product, boasts 1.5 billion monthly users—but fewer than 1% pay for it. That’s not a business model—it’s a popularity contest.

Yet Altman isn’t calling for a crash. He’s calling for clarity. His point is that bubbles form around kernels of truth—and AI’s kernel is enormous.

From autonomous agents to enterprise integration in law, medicine, and finance, the technology is reshaping workflows faster than regulators can blink.

Microsoft and Nvidia are pouring billions into infrastructure, not because they’re chasing hype, but because they see utility. Real utility.

Still, Altman’s warning is timely. The AI gold rush has spawned a legion of startups with dazzling demos and dismal revenue. This is likely the Dotcom ‘Esque’ reality – many will fail.

Many are burning cash at unsustainable rates, betting on future breakthroughs that may never materialise. Investors, Altman suggests, need to recalibrate—not abandon ship, but stop treating every chatbot as the next Google.

What makes Altman’s stance compelling is its duality. He’s not a doomsayer, nor a blind optimist. He’s a realist who understands that transformative tech often arrives wrapped in irrational exuberance. The internet had its crash before it changed the world. AI may follow suit.

So, is this a bubble? Yes. But it’s a bubble with brains. And if Altman’s lighthouse holds, it might just guide us through the fog—not to safety, but to something truly revolutionary.

In the meantime, investors would do well to remember hype inflates, but only utility sustains.

And Altman, ever the ‘paradoxical prophet’, seems to be betting on both.

China’s new AI model GLM-4.5 threatens DeepSeek – will it also threaten OpenAI?

China's AI

In a bold move reshaping the global AI landscape, Chinese startup Z.ai has launched GLM-4.5, an open-source model touted as cheaper, smaller, and more efficient than rivals like DeepSeek.

The announcement, made at the World Artificial Intelligence Conference in Shanghai, has sent ripples across the tech sector.

What sets GLM-4.5 apart is its lean architecture. Requiring just eight Nvidia H20 chips—custom-built to comply with U.S. export restrictions—it slashes operating costs dramatically.

By comparison, DeepSeek’s model demands nearly double the compute power, making GLM-4.5 a tantalising alternative for cost-conscious developers and enterprises.

But the savings don’t stop there. Z.ai revealed that it will charge just $0.11 per million input tokens and $0.28 per million output tokens. In contrast, DeepSeek R1 costs $0.14 for input and a hefty $2.19 for output, putting Z.ai firmly in the affordability lead.

Functionally, GLM-4.5 leverages ‘agentic’ AI—meaning it can deconstruct tasks into subtasks autonomously, delivering more accurate results with minimal human intervention.

This approach marks a shift from traditional logic-based models and promises smarter integration into coding, design, and editorial workflows.

Z.ai, formerly known as Zhipu, boasts an impressive funding roster including Alibaba, Tencent, and state-backed municipal tech funds.

With IPO ambitions on the horizon, its momentum mirrors China’s broader push to dominate the next wave of AI innovation.

While the U.S. has placed Z.ai on its entity list, stifling some Western partnerships, the firm insists it has adequate computing resources to scale.

As AI becomes a battleground for technological and geopolitical influence, GLM-4.5 may prove to be a powerful competitor.

But it has some way yet to go.

Microsoft joins Nvidia in the $4 trillion Market Cap club

Microdift and Nvidia only two companies in exclusive $4 trillion market cap club

In a landmark moment for the tech industry, Microsoft has officially joined Nvidia in the exclusive $4 trillion market capitalisation club, following a surge in its share price after stellar Q4 earnings.

This accolade achieved on 31st July 2025 marks a dramatic shift in the hierarchy of global tech giants, with Microsoft briefly overtaking Nvidia to become the world’s most valuable company. But for how long?

The rally was fuelled by Microsoft’s aggressive investment in artificial intelligence and cloud infrastructure. Azure, its cloud platform, posted a 39% year-on-year revenue increase, surpassing $75 billion in annual sales.

The company’s Copilot AI tools, now boasting over 100 million monthly active users, have become central to its strategy, embedding generative AI across productivity software, development platforms, and enterprise services.

Microsoft’s transformation from a traditional software provider to an AI-first powerhouse has been swift and strategic. Its partnerships with OpenAI, Meta, and xAI, combined with over $100 billion in planned capital expenditure, signal a long-term commitment to shaping the future of AI utility.

While Nvidia dominates the hardware side of the AI revolution, Microsoft is staking its claim as the platform through which AI is experienced.

This milestone not only redefines Microsoft’s legacy—it redraws the map of pure tech power and reach the company has around the world.

This has been earned over decades of business commitment.

Nvidia regains top spot by market cap

Nvidia top value company again

Nvidia has once again claimed the title of the world’s most valuable publicly traded company, overtaking Microsoft with a staggering market capitalisation of $3.76 trillion.

This milestone follows a 4% surge in Nvidia’s share price, closing at an all-time high of $154.10.

The rally was fuelled by renewed investor enthusiasm for artificial intelligence. Analysts citing it as a ‘Golden Wave’ of generative AI adoption driving demand for Nvidia’s high-performance chips.

The company’s meteoric rise has been underpinned by its dominance in AI hardware, particularly its GPUs, which power everything from ChatGPT to enterprise-scale AI models.

Since bottoming out in early April 2025, Nvidia’s stock has soared more than 60%, far outpacing the broader tech market.

Founded in 1993 to produce graphics chips for gaming, Nvidia has transformed into the backbone of the AI revolution. Its accelerators are now essential infrastructure for companies like Microsoft, Meta, and Google.

Nvidia share price as of 25th June 2025 – a 3 month snapshot

Nvidia share price as of 25th June 2025 – a 3 month snapshot

Despite its rapid ascent, Nvidia’s valuation remains relatively modest compared to historical norms, trading at around 30 times projected earnings.

As the AI arms race intensifies, Nvidia’s position at the summit of global markets underscores the growing importance of its power in shaping the digital future.

AMD Unveils Instinct MI400: is it time for AMD to challenge NVIDIA dominance?

AMD & NVIDIA chip go head-to-head

AMD has officially lifted the curtain on its next-generation AI chip, the Instinct MI400, marking a significant escalation in the battle for data centre dominance.

Set to launch in 2026, the MI400 is designed to power hyperscale AI workloads with unprecedented efficiency and performance.

Sam Altman and OpenAI have played a surprisingly hands-on role in AMD’s development of the Instinct MI400 series.

Altman appeared on stage with AMD CEO Lisa Su at the company’s ‘Advancing AI’ event, where he revealed that OpenAI had provided direct feedback during the chip’s design process.

Altman described his initial reaction to the MI400 specs as ‘totally crazy’ but expressed excitement at how close AMD has come to delivering on its ambitious goals.

He praised the MI400’s architecture – particularly its memory design – as being well-suited for both inference and training tasks.

OpenAI has already been using AMD’s MI300X chips for some workloads and is expected to adopt the MI400 series when it launches in 2026.

This collaboration is part of a broader trend: OpenAI, traditionally reliant on Nvidia GPUs via Microsoft Azure, is now diversifying its compute stack.

AMD’s open standards and cost-effective performance are clearly appealing, especially as OpenAI also explores its own chip development efforts with Broadcom.

AMD’s one-year chart snap-shot

One-year AMD chart snap-shot

So, while OpenAI isn’t ditching Nvidia entirely, its involvement with AMD signals a strategic shift—and a vote of confidence in AMD’s growing role in the AI hardware ecosystem.

At the heart of AMD’s strategy is the Helios rack-scale system, a unified architecture that allows thousands of MI400 chips to function as a single, massive compute engine.

This approach is tailored for the growing demands of large language models and generative AI, where inference speed and energy efficiency are paramount.

AMD technical power

The MI400 boasts a staggering 432GB of next-generation HBM4 memory and a bandwidth of 19.6TB/sec—more than double that of its predecessor.

With up to four Accelerated Compute Dies (XCDs) and enhanced interconnects, the chip delivers 40 PFLOPs of FP4 performance, positioning it as a formidable rival to Nvidia’s Rubin R100 GPU.

AMD’s open-source networking technology, UALink, replaces Nvidia’s proprietary NVLink, reinforcing the company’s commitment to open standards. This, combined with aggressive pricing and lower power consumption, gives AMD a compelling value proposition.

The company claims its chips can deliver 40% more AI tokens per dollar than Nvidia’s offerings.

Big tech follows AMD

OpenAI, Meta, Microsoft, and Oracle are among the major players already integrating AMD’s Instinct chips into their infrastructure. OpenAI CEO Sam Altman, speaking at the launch event reportedly praised the MI400’s capabilities, calling it ‘an amazing thing‘.

With the AI chip market projected to exceed $500 billion by 2028, AMD’s MI400 is more than just a product—it’s a statement of intent. As the race for AI supremacy intensifies, AMD is betting big on performance, openness, and affordability to carve out a larger share of the future.

It certainly looks like AMD is positioning the Instinct MI400 as a serious contender in the AI accelerator space – and Nvidia will be watching closely.

The MI400 doesn’t just aim to catch up; it’s designed to challenge Nvidia head-on with bold architectural shifts and aggressive performance-per-dollar metrics.

Nvidia has long held the upper hand with its CUDA software ecosystem and dominant market share, especially with the popularity of its H100 and the upcoming Rubin GPU. But AMD is playing the long game.

Nvidia 0ne-year chart snapshot

Nvidia 0ne-year chart snapshot

By offering open standards like UALink and boasting impressive specs like 432GB of HBM4 memory and 40 PFLOPs of FP4 performance, the MI400 is pushing into territory that was once Nvidia’s alone.

Whether it truly rivals Nvidia will depend on a few key factors: industry adoption, software compatibility, real-world performance under AI workloads, and AMD’s ability to scale production and support.

But with major players like OpenAI, Microsoft, and Meta already lining up to adopt the MI400.

Is now a good time to invest in AMD?

AI creates paradigm shift in computing – programming AI is like training a person

Teaching or programing?

At London Tech Week, Nvidia CEO Jensen Huang made a striking statement: “The way you program an AI is like the way you program a person.” (Do we really program people or do we teach)?

This marks a fundamental shift in how we interact with artificial intelligence, moving away from traditional coding languages and towards natural human communication.

Historically, programming required specialised knowledge of languages like C++ or Python. Developers had to meticulously craft instructions for computers to follow.

Huang argues that AI has now evolved to understand and respond to human language, making programming more intuitive and accessible.

This transformation is largely driven by advancements in conversational AI models, such as ChatGPT, Gemini, and Copilot.

These systems allow users to issue commands in plain English – whether asking an AI to generate images, write a poem, or even create software code. Instead of writing complex algorithms, users can simply ask nicely, much like instructing a colleague or student.

Huang’s analogy extends beyond convenience. Just as people learn through feedback and iteration, AI models refine their responses based on user input.

If an AI-generated poem isn’t quite right, users can prompt it to improve, and it will think and adjust accordingly.

This iterative process mirrors human learning, where guidance and refinement lead to better outcomes.

The implications of this shift are profound. AI is no longer just a tool for experts – it is a great equalizer, enabling anyone to harness computing power without technical expertise.

As businesses integrate AI into their workflows, employees will need to adapt, treating AI as a collaborative partner rather than a mere machine.

This evolution in AI programming is not just about efficiency; it represents a new era where technology aligns more closely with human thought and interaction.

Baidu, once China’s generative AI leader – is battling to regain its position

A Chatbot

Chinese tech giant Baidu has released two new free-to-use artificial intelligence models as it vies to regain its leading position in the country’s fiercely competitive AI space

The Baidu models launched on Sunday 16th March 2025 included the company’s first reasoning-focused model and come ahead of plans to move towards an open-source strategy. 

However, analysts reportedly said that while the release of the models is a positive development for Baidu, they also highlight how it is playing catch up as its Ernie bot – one of China’s earliest versions of a ChatGPT-like chatbot – struggles to gain widespread adoption. 

‘The new models make Baidu more competitive since the company has been lagging behind in a reasoning model release’, one expert is reported as saying.

A reasoning model is a large language model that breaks down tasks into smaller pieces and considers multiple approaches before generating a response. It is designed to process complex problems in a similar way to humans.

Chinese startup DeepSeek upended the global AI race and transformed China’s ecosystem in January when it released its R1 reasoning model, which rivalled American competitors despite costing a fraction of the price.

Artificial intelligence capable of matching humans at any task will be available within five ten years

AI

Artificial General Intelligence (AGI), a form of AI capable of matching or surpassing human intelligence across all tasks, is expected to emerge within the next five to ten years, according to Demis Hassabis, CEO of Google DeepMind.

Speaking recently, Hassabis highlighted the advancements in AI systems that are paving the way for AGI.

While current AI excels in specific domains, such as playing complex games like chess or Go – it still lacks the ability to generalise knowledge and adapt to real-world challenges.

But the advancements made in AI chatbots such as ChatGPT from OpenAI and DeepSeek have showcased remarkable development, and at speed too. Applying AI to work environments, science and domestic tasks is forever expanding.

Hassabis emphasised that significant research is still required to achieve AGI. The focus lies on improving AI’s understanding of context and its ability to plan and reason in dynamic environments.

Multi-agent systems, where AI entities collaborate or compete, are seen as a promising avenue for development.

These systems aim to replicate the intricate decision-making processes humans exhibit in complex scenarios.

The implications of AGI are profound, with potential applications spanning healthcare, education, and beyond.

However, its development also raises ethical and societal questions, including concerns about control, safety, and equitable access.

While the timeline remains speculative, Hassabis’s insights underscore the accelerating pace of AI innovation, bringing humanity closer to a future where machines and humans collaborate in unprecedented ways.

Or not?

Musk’s xAI releases new Grok 3 AI

xAI Grok AI

Elon Musk’s AI company, xAI, has recently released its latest AI model, Grok 3.

This new AI model is designed to be significantly more powerful and capable than its predecessor, Grok 2.
  • Enhanced Capabilities: Grok 3 boasts 10 times more computing power than Grok 2 and has been trained on an expanded dataset, including court case filings.
  • Reasoning Models: Grok 3 includes reasoning models that can carefully analyze and fact-check information before providing responses. This helps in avoiding common pitfalls of AI models.
  • Benchmark Performance: Grok 3 has outperformed other leading AI models, including OpenAI’s GPT-4o and DeepSeek’s R1, on various benchmarks such as AIME (math questions) and GPQA (physics, biology, chemistry problems).
  • New Features: The Grok app now includes a ‘DeepSearch’ feature that scans the internet and xAI’s social network, X, to provide summarised responses to user queries.
  • Subscription Plans: xAI has introduced a new subscription plan called SuperGrok, which offers additional reasoning capabilities and unlimited image generation.

Grok 3 is being hailed as the ‘smartest AI on Earth’ by Musk, and it’s expected to have a significant impact on various industries.

Definition

Grok is a neologism (a newly coined word or expression), referenced by Robert A. Heinlein for his 1961 science fiction novel Stranger in a Strange Land. It means to understand something so deeply that you become one with it.

Grok is a term used in computer programming to mean to ‘profoundly understand something‘, such as a system, a language, or an algorithm.

Less woke

Grok, the company previously reportedly said, is modelled on ‘The Hitchhiker’s Guide to the Galaxy’. 

It is supposed to have ‘a bit of wit, a rebellious streak’ and it should answer the ‘spicy questions’ that other AI might dodge, according to a statement from xAI.

I wonder if it has been modelled on Elon Musk?

Chinese tech giant Baidu to release next-generation AI model soon as DeepSeek leads Chinese AI tech

AI

China’s Baidu reportedly plans to release the next generation of its artificial intelligence model in the second half of this year, according to information recently reported.

The planned update comes as Chinese companies race to develop innovative AI models to compete with OpenAI and other U.S. based companies.

Baidu was the first major Chinese tech company to roll out a ChatGPT-like chatbot called Ernie in March 2023.

However, despite initial momentum, the product has since been eclipsed by other Chinese chatbots from large tech companies such as Alibaba and ByteDance, as well as startups.

The aftermath from the arrival of Deepseek

Deepseek AI

Nvidia, the renowned American technology company, recently experienced the largest one-day loss in U.S. history. On January 27, 2025, Nvidia’s stock plummeted by 17%, resulting in a staggering market cap loss of nearly $600 billion.

This unprecedented drop was primarily triggered by the emergence of DeepSeek, a Chinese artificial intelligence startup that has been making waves in the tech industry.

DeepSeek, founded in 2023 by Liang Wenfeng, has developed open-source large language models that rival some of the best AI models in the world. The company’s latest model, DeepSeek-V3, has demonstrated impressive performance at a fraction of the cost of its competitors.

This has raised concerns among investors about the sustainability of Nvidia’s dominance in the AI chip market.

The release of DeepSeek’s latest technology has caused significant anxiety among U.S. tech giants, leading to a massive sell-off in the stock market. Companies that rely heavily on Nvidia’s GPUs, such as Dell, Oracle, and Super Micro Computer, also saw their stock prices plummet.

The ripple effect of Nvidia’s loss was felt across the tech-heavy Nasdaq, which dropped by 3.1% on the same day.

Nvidia one-month chart 27th January 2025

In response to this market upheaval, former President Donald Trump commented on the situation, stating that DeepSeek’s emergence should serve as a ‘wake-up call’ for American companies.

Trump emphasised the need for U.S. industries to remain competitive and innovative in the face of rising competition from Chinese tech firms. He acknowledged the impressive advancements made by DeepSeek and suggested that American companies could benefit from adopting more cost-effective methods in their AI development.

Trump’s remarks highlight the growing concern among U.S. policymakers and industry leaders about the rapid advancements in AI technology coming from China.

The success of DeepSeek has demonstrated that significant breakthroughs can be achieved with relatively modest investments, challenging the notion that massive capital expenditure is necessary for top-tier AI performance.

As the AI race continues to heat up, it is clear that companies like Nvidia will need to adapt and innovate to maintain their competitive edge. The emergence of DeepSeek has not only disrupted the market but also underscored the importance of staying ahead in the rapidly evolving field of artificial intelligence.

For American tech giants, this wake-up call serves as a reminder that the global AI landscape is becoming increasingly competitive, and complacency is not an option.

Has the U.S. spent wisely on AI development?

The emergence of DeepSeek has indeed raised questions about the spending strategies of U.S. tech companies on AI development. DeepSeek’s ability to develop high-performing AI models at a fraction of the cost has led to concerns about the necessity of the massive capital expenditures by large U.S. tech firms.

For instance, companies like Microsoft, Alphabet, Meta, and Amazon have collectively spent over $1 trillion on AI investments in recent years. This significant spending has been driven by the belief that larger models and more computing power would lead to better performance.

However, DeepSeek’s success with more cost-effective methods challenges this notion and suggests that efficient innovation might be more important than sheer scale.

The impressive performance and lower costs of DeepSeek’s models have prompted some analysts to question whether the billions of dollars spent by U.S. tech companies on AI development are justified. This has led to a re-evaluation of AI spending strategies and a push for more efficient and innovative approaches to AI development.

In summary, while U.S. tech companies have invested heavily in AI, the success of DeepSeek highlights the potential for achieving cutting-edge results with fewer resources. This has sparked a broader discussion about the most effective and efficient ways to advance AI technology.

Asking ChatGPT – ‘Do you see Deepseek as a competitor or a threat?’

The reply:

As an AI, I don’t have personal opinions or feelings. However, I can share that DeepSeek’s rapid rise and impressive performance in the AI field are noteworthy. Their ability to develop high-performing models at a lower cost is a significant achievement and has certainly shaken up the industry. It’s a reminder of the dynamic and competitive nature of the AI landscape, where innovation can come from unexpected places.

Asking ChatGPT – ‘What do you think of Deepseek?’

The reply:

DeepSeek is a fascinating and disruptive player in the AI landscape. Founded in 2023 by Liang Wenfeng, this Chinese startup has quickly gained attention for its open-source large language models, which rival some of the best AI models in the world at a fraction of the cost. Their latest models, DeepSeek-V3 and DeepSeek-R1, have demonstrated impressive performance and efficiency, challenging the dominance of established tech giants2.

DeepSeek’s emergence has caused significant market upheaval, leading to substantial drops in the stock prices of major AI-related firms, including Nvidia. The company’s success highlights the potential for innovation and cost-effectiveness in AI development, which has prompted industry leaders and policymakers to re-evaluate their strategies.

Overall, DeepSeek’s rapid rise and impact on the AI industry underscore the importance of staying competitive and innovative in this fast-evolving field. It’s a reminder that breakthroughs can come from unexpected places and that the AI landscape is becoming increasingly dynamic and competitive.

It would not be drawn on these questions but, one thing is for sure the U.S. has spent billions developing their systems and charge fortunes for using it.

This is about to change.

And further…

The Deepseek website reportedly crashed on 27th January 2025 due to heavy global demand. There were also reports of unrelenting cyberattacks on its systems…?

Curious. From minnow to centre stage in just one day!

Google releases the first of its Gemini 2.0 AI models

Google AI

Google released the first version of its Gemini 2.0 family of artificial intelligence models in December 2024

Gemini 2.0 Flash, as the model is named is available in a chat version for users worldwide, while experimental multimodal version of the model, with text-to-speech image generation capabilities, available to developers.

‘If Gemini 1.0 was about organising and understanding information, Gemini 2.0 is about making it much more useful,’ Google CEO Sundar Pichai reportedly said in a statement.

Google’s latest large language model surpasses its predecessors in most user request areas, including code generation and the ability to provide factually accurate responses. However, it falls short compared to Gemini1.5 Pro when it comes evaluating longer contexts.

To access the chat-optimized version of the experimental Flash 2.0, Gemini users can select from the drop-down menu on both desktop and mobile web platforms. According to the company it will soon be available on the Gemini mobile app.

The multimodal version of Gemini Flash .0 will be accessible through Google’s AI Studio and Vertex AI developer platforms.

The general availability of Gemini 2.0 Flash’s multimodal version is scheduled for January, along with additional Gemini 2.0 model sizes, Google announced. The company also plans to expand Gemini 20 to more Google products in early 2025.

Gemini 2.0 signifies Google’s latest efforts in the increasingly competitive AI industry. Google is competing with major tech rivals such as Microsoft and Meta, as well as startups like OpenAI, the creator of ChatGPT, Perplexity, and Anthropic, which developed Claude.

In addition to new Flash, other research prototypes are aimed at developing more ‘agentic’ AI models and experiences. According to the company, agentic models ‘can understand more about the world around you, think multiple steps ahead, and take action on your behalf, with your supervision’.

Why has Sumsung fallen behind in the AI boom?

A Cartoon AI chip

Samsung’s struggle in the AI race

Samsung, previously a powerhouse in the semiconductor industry, has encountered significant hurdles in the AI competition, leading to a notable decline in market value. The company’s faltering stance can be attributed to a variety of factors, such as strategic errors, fierce competition, and swift technological progress in the AI field.

Missteps

A key factor in Samsung’s downturn in the AI sector is its insufficient investment in high-bandwidth memory (HBM) technology, which is vital for AI applications due to its ability to expedite data processing and enhance performance.

Although Samsung was once at the forefront of memory technology, it did not leverage the increasing demand for HBM, thus ceding ground to competitors such as SK Hynix. SK Hynix made significant investments in HBM and forged a robust partnership with Nvidia, an influential entity in the AI domain.

Competition

The AI sector is fiercely competitive, featuring key companies such as Nvidia, Google, and Microsoft, which are making substantial advancements in AI technology. Nvidia has notably become a frontrunner with its GPUs, crucial for AI training. Samsung’s struggle to match these developments has resulted in a decline in both market share and revenue.

Rapid technological advancements

The swift advancement of technology in the AI sector has presented challenges for Samsung. The company’s emphasis on conventional memory technology did not fully prepare it for the transition to AI-centric applications. With the rise of AI applications such as OpenAI’s ChatGPT, the need for sophisticated memory solutions surged, highlighting Samsung’s insufficient investment in High-Bandwidth Memory (HBM) as a notable shortcoming.

Financial implications

Samsung’s difficulties in the AI sector have significantly affected its finances. The company has seen a reported loss of around $122 billion in market value since July 2024, marking the most substantial drop among global chipmakers. This decline is largely due to Samsung’s challenges in adapting to the evolving AI industry and competing with its rivals.

Prospects

Despite facing challenges, Samsung is actively striving to advance in the AI domain. The company has recently introduced its next-generation Bixby AI, which utilizes large language model technology, positioning it to better contend with competitors such as ChatGPT and Google Gemini.

Additionally, Samsung is cultivating its proprietary AI model, named Samsung Gauss, with the goal of augmenting device functionality and elevating the consumer experience.

Samsung’s lag in the AI sector is due to strategic errors, fierce competition, and swift technological progress. Despite considerable financial setbacks, the company is vigorously pursuing new AI initiatives and investments to recover its standing in the industry.

The path forward is fraught with challenges, yet Samsung’s commitment to innovation and adaptation could enable it to regain its status as a frontrunner in the AI domain.

Big tech companies are increasingly adopting nuclear power to meet the high energy demands of their AI data centres

Data centre powered by nuclear reactors

Why?

Elevated Energy Needs

AI systems, particularly generative AI, necessitate substantial computational power, leading to significant energy use. Conventional energy sources might not meet these growing demands.

Environmental Commitments

Numerous tech firms have pledged to lower their carbon emissions. Nuclear power, a low-emission energy source, supports these environmental commitments.

Dependability

Nuclear energy offers a consistent and uninterrupted power supply, essential for data centres that operate around the clock.

Technological Advancements

Progress in nuclear technologies, such as small modular reactors (SMRs), has enhanced the feasibility and appeal of nuclear power for extensive use.

For example, Google has entered into an agreement with Kairos Power for electricity from small modular reactors to bolster its AI operations. In a similar vein, Microsoft has collaborated with Constellation to refurbish an inactive reactor at the Three Mile Island nuclear facility.

These collaborations mark a notable transition in the energy strategies of the tech sector, as they pursue dependable, eco-friendly, and robust power solutions to support their AI initiatives.

Nvidia hits new record high with new $3.4 trillion market cap

AI chips

Nvidia’s shares have reached a record peak as the company continues to benefit from the surging demand for its AI chips

Tech giants such as Microsoft, Meta, Google, and Amazon are acquiring Nvidia’s GPUs in large volumes to create extensive AI computing clusters.

Nvidia, with a market capitalisation of around $3.4 trillion, ranks as the second most valuable publicly traded company in the U.S., trailing behind Apple, which has a market cap of approximately $3.55 trillion.

And to think… just 6 weeks ago Nvidia hit the news with this headline: Nvidia $279 billion market cap wipeout — the biggest in U.S. history for just ONE company.

Oh, the volatility of tech stocks, don’t you just love it?

The company’s stock rose by 2.4% to close at $138.07, exceeding the previous high of $135.58 set on 18th June 2023. The shares have increased by nearly 180% this year and have experienced a more than ninefold increase since early 2023.

Regarded as the leading supplier in the AI revolution, Nvidia has gained significantly from the generative AI surge initiated by OpenAI’s ChatGPT release in November 2022. Nvidia’s GPUs are instrumental in developing and running sophisticated AI models, including those that operate ChatGPT and related platforms.

You can’t go far wrong when big players such as Microsoft, Meta, Google and Amazon are buying your stuff.

Meta reportedly to use the voice of Dame Judi Dench for its celebrity AI Chatbot

Chatbot with celebrity voices

Meta, the parent company of Instagram, has announced that voices of Dame Judi Dench and John Cena will be available as options for its AI chatbot.

Moreover, users can access information through AI representations of celebrities such as Awkwafina, Keegan-Michael Key, and Kristen Bell. Meta is hopeful that this new endeavour with celebrity chatbots will surpass the success of its previous attempts. In September 2023, Meta introduced AI chatbots featuring the ‘personalities’ of celebrities including Kendall Jenner and Snoop Dogg, but the project was terminated within a year.

At Meta’s annual Connect conference, CEO Mark Zuckerberg announced the new celebrity chatbot project, remarking, ‘Interacting with AI through voice will be more intuitive than through text.‘ The enhanced ChatGPT-style chatbot will also be capable of recognizing objects in images and providing relevant details. Additionally, a novel image editing tool will allow users to alter photos by simply directing the Meta AI with their requests.

Meta has disclosed that its AI now reaches over 400 million people monthly, with 185 million engaging weekly.

Meta one-year chart as of 2nd October 2024

Meta one-year chart as of 2nd October 2024

What is China’s equivalent to Nvidia?

AI microchips

Chinese firms are reportedly intensifying their efforts to develop a competitive alternative to Nvidia’s AI chips, as part of Beijing’s ongoing initiative to reduce its reliance on U.S. technology.

China faces several challenges that are impeding its technological progress, including U.S. export restrictions that limit domestic semiconductor production. The lack of technical expertise is also reported to be a problem.

Analysts have identified companies including Huawei as the principal competitors to Nvidia in China

China’s counterparts to Nvidia, such as Huawei, Alibaba, and Baidu, are actively developing AI chips to compete in the same market. Huawei’s HiSilicon division is known for its Ascend series of data centre processors.

Huawei’s HiSilicon division is known for its Ascend series of data centre processors, and Alibaba’s T-Head has produced the Hanguang 800 AI inference chip. Other significant players include Biren Technology and Cambricon Technologies.

Alibaba’s T-Head has developed the Hanguang 800 AI inference chip. Other significant players include Biren Technology and Cambricon Technologies.

These Chinese firms are intensifying their efforts to create alternatives to Nvidia’s AI-powering chips. This is a big part of Beijing’s broader initiative to reduce its reliance on U.S. technology.

Nvidia’s surge in growth is attributed to the demand from major cloud computing companies for its server products, which incorporate graphics processing units, or GPUs.

These GPUs are crucial for entities like OpenAI, the creator of ChatGPT, which requires substantial computational power to train extensive AI models on large datasets.

AI models are crucial for chatbots and other AI applications

Since 2022, the U.S. has limited the export of Nvidia’s top-tier chips to China, with further restrictions imposed last year.

The U.S. sanctions and Nvidia’s market dominance pose significant obstacles to China’s ambitions, particularly in the short term, according to analysts. The U.S. has curbed the export of Nvidia’s most sophisticated chips to China since 2022, with increased restrictions implemented last year.

China’s GPU designers rely on external manufacturers for chip production. Traditionally, this role was filled by Taiwan Semiconductor Manufacturing Co. (TSMC). However, due to U.S. restrictions, many Chinese firms are now unable to procure chips from TSMC.

As a result, they have shifted to using SMIC, China’s largest chipmaker, which is technologically several generations behind TSMC. This gap is partly due to Washington’s limitations on SMIC’s access to essential machinery from the Dutch company ASML, necessary for producing the most advanced chips.

Huawei is driving the development of more sophisticated chips for its smartphones and AI, which occupies a significant portion of SMIC’s capacity.

Nvidia has achieved success not only through its advanced semiconductors but also via its CUDA software platform. The system enables developers to build applications for Nvidia’s hardware. This has fostered an ecosystem around Nvidia’s designs, which will be challenging for competitors to emulate.

Huawei leading the pack for China

Huawei is at the forefront as a leading force in China for its Ascend series of data centre processors. The current generation, named Ascend 910B, is soon to be succeeded by the Ascend 910C. This new chip may come to rival Nvidia’s H100.

The AI Race between China and the U.S.

AI development in China and U.S.

Artificial Intelligence (AI) has become a pivotal battleground in the technological race between China and the United States.

“AI is expected to become a crucial component of economic and military power in the near future,” Stanford University’s Artificial Intelligence Index Report 2023 stated.

Both countries are significantly investing in AI research and development, striving to achieve a leading role in this revolutionary sector. This post looks at the major figures in China’s AI scene, their progress, and their comparison with their American counterparts.

China’s AI Landscape

China’s AI aspirations are propelled by a number of significant technology firms, each forging their own AI models and applications.

Baidu: Often referred to as the ‘Google of China,’ Baidu leads in AI development. Its premier AI model, ERNIE (Enhanced Representation through Knowledge Integration), fuels the Ernie Bot, a chatbot aimed to compete with OpenAI’s ChatGPT. Baidu asserts that ERNIE 4.0 matches GPT-4’s capabilities, demonstrating sophisticated understanding and reasoning abilities.

Alibaba: Alibaba’s AI model, Tongyi Qianwen (commonly known as Qwen), is a comprehensive set of foundational models adept at a range of tasks, from generating content to solving mathematical problems. Select versions of Qwen are open-source, enabling developers to utilize and modify them for various uses. Alibaba has announced that Qwen models are in use by over 90,000 enterprise clients.

Tencent: The Hunyuan model from Tencent is a prominent component of China’s AI landscape. Offered through Tencent’s cloud computing division, Hunyuan is tailored to facilitate a broad spectrum of applications, encompassing natural language processing and computer vision.

Huawei: In spite of considerable obstacles stemming from U.S. sanctions, Huawei persists in AI innovation. The firm has created its own AI processors, like the Kunlun series, to diminish dependence on international technology. Huawei’s AI features are incorporated into a diverse array of products, including smartphones and cloud solutions.

Comparison to the U.S.

The U.S. continues to be a dominant force in AI, with leading companies such as OpenAI, Microsoft, Google, Anthropic and Meta spearheading advancements.

Generative AI: U.S. firms have advanced significantly in generative AI, with OpenAI’s GPT-4 and Google’s Gemini at the forefront. These models excel in creating text, images, and videos from user inputs. Although Chinese models like ERNIE and Qwen are strong contenders, the U.S. maintains a slight lead in capabilities and market penetration.

Semiconductor Design: The U.S. leads the semiconductor design industry, vital for AI progress. U.S. companies command an 85% global market share in chip design, crucial for AI model training and system operation. China’s dependence on imported semiconductors is a notable obstacle, but there are ongoing efforts to create homegrown solutions.

Research and Innovation: Both nations boast strong AI research sectors, yet the U.S. edges out slightly in generating state-of-the-art AI products. U.S. tech giants frequently introduce AI breakthroughs to the market, with Chinese firms quickly gaining ground.

Government Support: The Chinese government ardently backs AI advancement, enacting strategies to spur innovation and lessen foreign tech reliance. Such support has spurred China’s AI industry’s rapid expansion, positioning it as a strong rival to the U.S.

Conclusion

The competition in AI development between China and the U.S. is escalating, as both countries achieve significant breakthroughs. Although the U.S. maintains a marginal lead in some respects, China’s swift advancement and state backing indicate that the disparity might keep closing. The quest for AI dominance by these nations is set to influence the worldwide technological and innovative landscape profoundly.

As of September 2024, it is estimated that China’s AI development is approximately nine months behind that of the U.S.

Microsoft to release Windows Recall AI search feature for testing as soon as October 2024

AI enabled local device

Microsoft announced on Wednesday 21st August 2024 that it will release the contentious Recall AI search feature for Windows users to test starting in October

Recall captures screenshots of on-screen activity, enabling users to search for previously seen information. Security experts raised immediate concerns about the potential risks of Windows capturing images automatically without user consent. In response, researchers developed open-source software demonstrating how attackers could easily access personal information.

Microsoft addressed these concerns in June 2024, stating that Recall would be disabled by default and promising security improvements for the feature.

While Microsoft has not provided a specific timeline for a wider release, it has introduced a new category of Windows PCs, termed Copilot+ PCs, which meet the system requirements for Recall. These PCs, produced by various manufacturers, are designed to handle AI workloads, and Microsoft has demonstrated Recall operating on these devices.

*Manufacturers are eager to demonstrate that AI models can run on local PCs, offering an alternative to cloud-based servers from companies like OpenAI. Following this trend, Apple has launched MacBooks capable of running AI models, and Microsoft’s latest Surface Pro is also a Copilot+ PC with local AI capabilities.

The timing of Recall’s broader release could be pivotal, as consumer interest in new computers may spike during the holiday season if Microsoft extends Recall to all compatible devices by that time.

*Is this a move away from AI cloud-based operations to some extent? AI tasks can easily be run in the cloud – why do we need an AI enabled device?

Microsoft says OpenAI is now a competitor search and AI

AI competition

Microsoft’s list of competitors, which is updated regularly, now features OpenAI, previously a long-term strategic ally.

This development follows OpenAI’s announcement of a search engine prototype.

As OpenAI’s exclusive cloud provider, Microsoft leverages OpenAI’s AI models for products aimed at commercial clients and consumers. Microsoft, OpenAI’s largest investor, has reportedly invested some $13 billion in the firm.

Microsoft’s filing lists OpenAI, the entity behind the ChatGPT chatbot, as a competitor in AI solutions, as well as in the realms of search and news advertising. OpenAI recently unveiled a search engine prototype named SearchGPT.

However, recent developments suggest a shift, with both companies encroaching on each other’s domains.

While some opt to directly pay OpenAI for model access, others utilise Microsoft’s Azure OpenAI Service. Additionally, Microsoft offers the Copilot chatbot as an alternative to ChatGPT, accessible via the Bing search engine and Windows operating systems.

OpenAI announces a search engine called SearchGPT

A new powerful search engine

OpenAI on Thursday 25th July 2024 announced a prototype of its search engine, called SearchGPT, which aims to give users “fast and timely answers with clear and relevant sources.”

The company has announced plans to eventually incorporate the tool, presently in testing with a select user group, into its ChatGPT chatbot.

The introduction of ChatGPT could have significant implications for Google’s search engine dominance. Since ChatGPT’s debut in November 2022, there has been growing concern among Alphabet’s investors that OpenAI may capture a portion of Google’s market share by offering consumers innovative methods to obtain information on the internet.

Alphabet three month share price as of 25th July 2024

Alphabet three month share price as of 25th July 2024

OpenAI’s ChatGPT was incorporated into Microsoft’s search engine Bing as Copilot and the companies have kept market dominance with this shrewd AI move. Google, on the other hand, has struggled to keep up in the AI race and may now be suffering the effects.

This announcement could have implications for Microsoft’s Copilot as well.

Apple finally now has AI and it’s called: Apple Intelligence (AI)

AI

Apple has entered the artificial intelligence race with the announcement of its version of AI – Apple Intelligence on Monday 10th June 2024, in its attempt to catch up in the AI race.

Reportedly to use it on your phone, you’ll need at least the high-end iPhone 15 Pro from this year’s lineup.

According to Apple’s website, Apple Intelligence will also be compatible with devices equipped with the M1 chip, including the iPad Air, iPad Pro, and Macs.

Apple Intelligence, set to launch in beta this autumn, will offer a variety of features. It will be able to proofread and rewrite your text in different tones, create personalized emojis known as ‘Genmoji,‘ and search for specific messages on your iPhone.

Additionally, it will summarize and transcribe phone calls, manage priority notifications, and integrate OpenAI’s ChatGPT for enhanced Siri responses.

Nothing new here then, just AI features already available elsewhere. Hopefully it will have a decent Apple AI make-over when it finally and fully arrives across all Apple products and platforms.

Apple isn’t leading in AI… yet – it’s just following for now!

Little know company Kneron launches latest AI chips – backed by Qualcomm

AI chip

Kneron, a startup specializing in artificial intelligence chips, unveiled its latest products on Wednesday 4th June 2024.

The company aims to exploit the growing world-wide interest in AI and provide an alternative to industry heavyweights such as Nvidia and AMD.

The company, headquartered in Taiwan and supported by American semiconductor leader Qualcomm and major iPhone assembler Foxconn, introduced the KNEO 330, its second-generation ‘edge GPT’ server.

GPT, short for generative pre-trained transformer, is an AI algorithm trained on vast datasets capable of generating text and images, with OpenAI’s ChatGPT being the world leader right now.

Cisco’s ThousandEyes has unveiled an AI product designed to predict and rectify internet outages

AI net

ThousandEyes, Cisco’s internet monitoring division, has introduced a new suite of AI-driven features known as Digital Experience Assurance, or DXA, on Tuesday 4th June 2024.

The firm asserts that this new AI technology will allow customers to not only monitor but also automatically address issues affecting network quality.

Describing itself as the ‘Google Maps’ of the internet, Cisco ThousandEyes offers a comprehensive, end-to-end perspective of every user and application across all networks.

Established 15 years prior, the company has been heavily investing in AI technology in recent years.

ThousandEyes is now implementing significant AI-centric modifications to its platform, which are designed to enhance its clients’ oversight of network quality and robustness.

Bitcoin miners rotate millions into AI – but why?

Bitcoin mining

Bitcoin miners have been diversifying operations into artificial intelligence (AI) due to several key factors.

Since Bitcoin halving, miners have been searching for more lucrative income streams as AI and crypto industries collide.

Revenue shift

The revenue from crypto mining, especially Bitcoin, has significantly decreased in recent months. After the ‘Bitcoin halving’ event in April 2024, rewards earned by Bitcoin miners were cut by 50%. As a result, miners have been seeking alternative revenue streams.

AI boom

Following the unveiling of ChatGPT by OpenAI in November 2022, there has been a significant increase in the demand for AI computation and infrastructure. This surge has led to a flurry of investments in AI models and startups, presenting miners with new opportunities to transition into the AI sector.

Energy access

Bitcoin miners are progressively turning to ‘stranded energy site’s – these are locations with surplus or untapped energy for mining operations. At the same time, they are channelling investments into AI at more stable sites. This strategic move enables them to leverage the potentially higher returns from AI.

Core Scientific

Core Scientific, a Bitcoin mining company, has recently entered into a 12-year agreement with cloud provider CoreWeave to supply infrastructure for AI applications. This partnership is anticipated to generate in excess of $3.5 billion in revenue over the duration of the contract. CoreWeave, supported by Nvidia, offers rental of graphics processing units (GPUs) essential for AI model training.

In conclusion, Bitcoin miners are increasingly adopting AI to adjust to the evolving market dynamics and to uncover new revenue streams beyond conventional mining. The merging of AI and the cryptocurrency industry offers promising prospects for both fields.

OpenAI launches new AI model – and it talks, sees and hears!

Chatbot GPT-4o

OpenAI has just unveiled its latest flagship model, GPT-4o. This remarkable model can reason across audio, vision, and text in real time.

Multimodal interaction

GPT-4o accepts any combination of text, audio, and image as input and generates corresponding outputs in any of these modalities. It’s a step toward more natural human-computer interaction.

Fast response time

GPT-4o can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds – similar to human conversation speed.

Improved language understanding

It matches GPT-4 Turbo performance on English text and code, with significant improvements in non-English languages. Plus, it’s 50% cheaper in the API.

Vision and audio understanding

GPT-4o excels in understanding images and audio compared to existing models.

Training

Unlike previous Voice Mode (which used separate models), GPT-4o is trained end-to-end across text, vision, and audio. This means it processes all inputs and outputs using the same neural network.

Exploring capabilities

OpenAI is still exploring what GPT-4o can do and its limitations. It’s a promising step toward more versatile AI interactions.

More here on the OpenAI website