Tag: Copilot

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Nvidia Q3 results were very strong – but does the AI bubble reside elsewhere – such as with the debt driven AI data centre roll out – and crossover company deals?

AI debt

Nvidia’s Q3 results show strength, but the real risk of an AI bubble may lie in the debt-fuelled data centre boom and the circular crossover deals between tech giants.

Nvidia’s latest quarterly earnings were nothing short of spectacular. Revenue surged to $57 billion, up 62% year-on-year, with net income climbing to nearly $32 billion. The company’s data centre division alone contributed $51.2 billion, underscoring how central AI infrastructure has become to its growth.

These figures have reassured investors that Nvidia itself is not the weak link in the AI story. Yet, the question remains: if not Nvidia, where might the bubble be forming?

Data centre roll-out

The answer may lie in the debt-driven expansion of AI data centres. Building hyperscale facilities requires enormous capital outlays, not only for GPUs but also for power, cooling, and connectivity.

Many operators are financing this expansion through debt, betting that demand for AI services will continue to accelerate. While Nvidia’s chips are sold out and cloud providers are racing to secure supply, the sustainability of this debt-fuelled growth is less certain.

If AI adoption slows or monetisation lags, these projects could become overextended, leaving balance sheets strained.

Crossover deals

Another area of concern is the crossover deals between major technology companies. Nvidia’s Q3 was buoyed by agreements with Intel, OpenAI, Google Cloud, Microsoft, Meta, Oracle, and xAI.

These arrangements exemplify a circular investment pattern: companies simultaneously act as customers, suppliers, and investors in each other’s AI ventures.

While such deals create momentum and headline growth, they risk masking the true underlying demand.

If much of the revenue is generated by companies trading capacity and investment back and forth, the market could be inflating itself rather than reflecting genuine end-user adoption.

Bubble or not to bubble?

This dynamic is reminiscent of past bubbles, where infrastructure spending raced ahead of proven returns. The dot-com era saw fibre optic networks built faster than internet businesses could monetise them.

Today, AI data centres may be expanding faster than practical applications can justify. Nvidia’s results prove that demand for compute is real and immediate, but the broader ecosystem may be vulnerable if debt levels rise and crossover deals obscure the true picture of profitability.

In short, Nvidia’s strength does not eliminate bubble risk—it merely shifts the spotlight elsewhere. Investors and policymakers should scrutinise the sustainability of AI infrastructure financing and the circular nature of tech partnerships.

The AI revolution is undoubtedly transformative, but its foundations must rest on genuine demand rather than speculative debt and self-reinforcing deals.

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Anthropic’s ‘connected’ AI deal and others too

Anthropic's AI valuation

Anthropic has reportedly struck major deals with Microsoft and Nvidia. On Tuesday 18th November 2025, Microsoft announced plans to invest up to $5 billion in the startup, while Nvidia will contribute as much as $10 billion. According to a reports, this brings Anthropic’s valuation to around $350 billion. Wow!

Google has unveiled its newest AI model, Gemini 3. According to Alphabet CEO Sundar Pichai, it will deliver desired answers with less prompting.

This update comes just eight months after the launch of Gemini 2.5 and is reported to be available in the coming weeks.

Money keeps flowing

Money keeps flowing into artificial intelligence companies but out of AI stocks

In what seems like yet another case of mutual ‘back-scratching’, Microsoft and Nvidia are set to invest a combined $15 billion in Anthropic, with the OpenAI rival agreeing to purchase computing power from its two newest backers.

Lately, a large chunk of AI news feels like it boils down to: ‘Company X invests in Company Y, and Company Y turns around and buys from Company X’.

That’s not entirely correct or fair. There are plenty of advancements in the AI world that focus on actual development rather than investments. Google recently introduced the third version of Gemini, its AI model.

Anthropic’s valuation has surged to around $350 billion, propelled by a landmark $15 billion investment from Microsoft and Nvidia.

Anthropic, the AI start-up founded in 2021 by former OpenAI employees, has rapidly ascended into the ranks of the world’s most valuable companies, more than doubling its worth from $183 billion just a few months earlier.

A valuation of $350 billion for a company only 4 years old is astounding!

The deal reportedly sees Microsoft commit up to $5 billion and Nvidia up to $10 billion. Anthropic has agreed to purchase an extraordinary $30 billion in Azure compute capacity and additional infrastructure from Nvidia.

This strategic alliance is not merely financial; it signals a deliberate diversification of Microsoft’s AI ecosystem beyond its reliance on OpenAI. And Nvidia strengthens its dominance in AI hardware.

Anthropic’s valuation has reached $350 billion, following the massive $15 billion investment from Microsoft and Nvidia, which positions the company among the most valuable in the world.

This astronomical figure reflects both the scale of its partnerships — including $30 billion in Azure compute commitments and Nvidia’s cutting-edge hardware.

The valuation underscores both the intensity of the global AI race and the confidence investors place in Anthropic’s safety-conscious approach to artificial intelligence.

Yet, it also raises questions about whether such astronomical figures reflect genuine long-term value. Or is it the froth of an overheated market.

Hyperscalers keep pumping the money into AI but are they getting the justified returns yet? Probably not yet – but it will come in the future.

But by then, it will be time to upgrade the system as it develops and so more money will be pumped in

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Markets on a Hair Trigger: Trump’s Tariff Whiplash and the AI Bubble That Won’t Pop

Markets move as Trump tweets

U.S. stock markets are behaving like a mood ring in a thunderstorm—volatile, reactive, and oddly sentimental.

One moment, President Trump threatens a ‘massive increase’ in tariffs on Chinese imports, and nearly $2 trillion in market value evaporates.

The next, he posts that: ‘all will be fine‘, and futures rebound overnight. It’s not just policy—it’s theatre, and Wall Street is watching every act with bated breath.

This hypersensitivity isn’t new, but it’s been amplified by the precarious state of global trade and the towering expectations placed on artificial intelligence.

Trump’s recent comments about China’s rare earth export controls triggered a sell-off that saw the Nasdaq drop 3.6% and the S&P 500 fall 2.7%—the worst single-day performance since April.

Tech stocks, especially those reliant on semiconductors and AI infrastructure, were hit hardest. Nvidia alone lost nearly 5%.

Why so fickle? Because the market’s current rally is built on a foundation of hope and hype. AI has been the engine driving valuations to record highs, with companies like OpenAI and Anthropic reaching eye-watering valuations despite uncertain profitability.

The IMF and Bank of England have both warned that we may be in stage three of a classic bubble cycle6. Circular investment deals—where AI startups use funding to buy chips from their investors—have raised eyebrows and comparisons to the dot-com era.

Yet, the bubble hasn’t burst. Not yet. The ‘Buffett Indicator‘ sits at a historic 220%, and the S&P 500 trades at 188% of U.S. GDP. These are not numbers grounded in sober fundamentals—they’re fuelled by speculative fervour and a fear of missing out (FOMO).

But unlike the dot-com crash, today’s AI surge is backed by real infrastructure: data centres, chip fabrication, and enterprise adoption. Whether that’s enough to justify the valuations remains to be seen.

In the meantime, markets remain twitchy. Trump’s tariff threats are more than political posturing—they’re economic tremors that ripple through supply chains and investor sentiment.

And with AI valuations stretched to breaking point, even a modest correction could trigger a cascade.

So yes, the market is fickle. But it’s not irrational—it’s just balancing on a knife’s edge between technological optimism and geopolitical anxiety.

One tweet can tip the scales.

Fickle!

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AI Crash! Correction or pullback? Something is coming…

AI Bubble concerns

Influential figures and institutions are sounding the AI alarm—or at least raising eyebrows—about the frothy valuations and speculative fervour surrounding artificial intelligence.

Who’s Warning About the AI Bubble?

🏛️ Bank of England – Financial Policy Committee

  • View: Stark warning.
  • Quote: “The risk of a sharp market correction has increased.”
  • Why it matters: The BoE compares current AI stock valuations to the dotcom bubble, noting that the top five S&P 500 firms now command nearly 30% of market cap—the highest concentration in 50 years.

🏦 Jerome Powell – Chair, U.S. Federal Reserve

  • View: Cautiously sceptical.
  • Quote: Assets are “fairly highly valued.”
  • Why it matters: While not naming AI directly, Powell’s remarks echo broader concerns about tech valuations and investor exuberance.

🧮 Lisa Shalett – Chief Investment Officer, Morgan Stanley Wealth Management

  • View: Deeply concerned.
  • Quote: “This is not going to be pretty” if AI capital expenditure disappoints.
  • Why it matters: Shalett warns that 75% of S&P 500 returns are tied to AI hype, likening the moment to the “Cisco cliff” of the early 2000s.

🌍 Kristalina Georgieva – Managing Director, IMF

  • View: Watchful.
  • Quote: Financial conditions could “turn abruptly.”
  • Why it matters: Georgieva highlights the fragility of markets despite AI’s productivity promise, warning of sudden sentiment shifts.

🧨 Sam Altman – CEO, OpenAI

  • View: Self-aware caution.
  • Quote: “People will overinvest and lose money.”
  • Why it matters: Altman’s admission from inside the AI gold rush adds credibility to bubble concerns—even as his company fuels the hype.

📦 Jeff Bezos – Founder, Amazon

  • View: Bubble-aware.
  • Quote: Described the current environment as “kind of an industrial bubble.”
  • Why it matters: Bezos sees parallels with past tech manias, suggesting that infrastructure spending may be overextended.

🧠 Adam Slater – Lead Economist, Oxford Economics

  • View: Analytical.
  • Quote: “There are a few potential symptoms of a bubble.”
  • Why it matters: Slater points to stretched valuations and extreme optimism, noting that productivity projections vary wildly.

🏛️ Goldman Sachs – Investment Strategy Division

  • View: Cautiously optimistic.
  • Quote: “A bubble has not yet formed,” but investors should “diversify.”
  • Why it matters: Goldman acknowledges the risks while maintaining that fundamentals may still justify valuations—though they advise caution.
AI Bubble voices infographic October 2025

🧠 Julius Černiauskas and the Oxylabs AI/ML Advisory Board

🔍 View: The AI hype is nearing its peak—and may soon deflate.

  • Černiauskas warns that AI development is straining environmental resources and public trust. He’s pushing for responsible and sustainable AI practices, noting that transparency is lacking in how many models operate.
  • Ali Chaudhry, research fellow at UCL and founder of ResearchPal, adds that scaling laws are showing their limits. He predicts diminishing returns from simply making models bigger, and expects tightened regulations around generative AI in 2025.
  • Adi Andrei, cofounder of Technosophics, goes further: he believes the Gen AI bubble is on the verge of bursting, citing overinvestment and unmet expectations

🧠 Jamie Dimon on the AI Bubble

🔥 View: Sharply concerned—more than most as widely reported

  • Quote: “I’m far more worried than others about the prospects of a downturn.”
  • Context: Dimon believes AI stock valuations are “stretched” and compares the current surge to the dotcom bubble of the late 1990s.

📉 Key Warnings from Dimon

  • “Sharp correction” risk: He sees a real danger of a sudden market pullback, especially given how AI-related stocks have surged disproportionately—like AMD jumping 24% in a single day after an OpenAI deal.
  • “Most people involved won’t do well”: Dimon told the BBC that while AI will ultimately pay off—like cars and TVs did—many investors will lose money along the way.
  • “Governments are distracted”: He criticised policymakers for focusing on crypto and ignoring real security threats, saying: “We should be stockpiling bullets, guns and bombs”.
  • “AI will disrupt jobs and companies”: At a trade event in Dublin, he warned that AI’s ubiquity will shake up industries and employment across the board.

And so…

The AI boom of 2025 has ignited a speculative frenzy across global markets, with tech stocks soaring and investors piling into anything labelled “AI-adjacent.”

But beneath the euphoria, a chorus of high-profile warnings is growing louder. From the Bank of England and IMF to JPMorgan’s Jamie Dimon and OpenAI’s Sam Altman, concerns are mounting that valuations are dangerously stretched, capital is overconcentrated, and the narrative is outpacing reality.

Dimon likens the moment to the dotcom bubble, while Altman admits many will “lose money” chasing the hype. Analysts point to classic bubble signals: retail mania, corporate FOMO, and earnings divorced from fundamentals.

Even as AI’s long-term utility remains promising, the short-term exuberance may be setting the stage for a sharp correction.

Whether it’s a pullback or a full-blown crash, the mood is shifting—from uncritical optimism to wary anticipation.

The question now is not whether AI will change the world, but whether markets have priced in too much, too soon.

We have been warned!

The AI bubble will pop – it’s just a matter of when and not if.

Go lock up your investments!

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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.

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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.

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China’s AI vs U.S. AI – competition heats up – and that’s good for business – isn’t it?

DeepSeek AI

The escalating AI competition between the U.S. and China has taken a new turn with the emergence of DeepSeek, a Chinese AI startup that has introduced a low-cost AI model capable of rivaling the performance of OpenAI’s models.

This development has significant implications for data centres and the broader technology sector.

The rise of DeepSeek

DeepSeek’s recent breakthrough involves the development of two AI models, V3 and R1, which have been created at a fraction of the cost compared to their Western counterparts.

The total training cost for these models is estimated at around $6 million, significantly lower than the billions spent by major U.S. tech firms. This has challenged the prevailing assumption that developing large AI models requires massive financial investments and access to cutting-edge hardware.

Impact on data centres

The introduction of cost-effective AI models like those developed by DeepSeek could lead to a shift in how data centers operate.

Traditional AI models require substantial computational power and energy, leading to high operational costs for data centers. DeepSeek’s models, which are less energy-intensive, could reduce these costs and make AI technology more accessible to a wider range of businesses and organizations.

Technological advancements

DeepSeek’s success also highlights the potential for innovation in AI without relying on the most advanced hardware.

This could encourage other companies to explore alternative approaches to AI development, fostering a more diverse and competitive landscape. Additionally, the open-source nature of DeepSeek’s models promotes collaborative innovation, allowing developers worldwide to customise and improve upon these models2.

Competitive dynamics

The competition between DeepSeek and OpenAI underscores the broader U.S.-China rivalry in the AI space. While DeepSeek’s models pose a limited immediate threat to well-funded U.S. AI labs, they demonstrate China’s growing capabilities in AI innovation.

This competition could drive both countries to invest more in AI research and development, leading to faster technological advancements and more robust AI applications.

Broader implications

The rise of DeepSeek and similar Chinese and other AI startups could have far-reaching implications for the global technology sector.

As AI becomes increasingly integrated into various industries, the ability to develop and deploy AI models efficiently will be crucial.

Data centres will need to adapt to these changes, potentially investing in more energy-efficient infrastructure and exploring new ways to support AI workloads.

Where from here?

DeepSeek’s emergence as a significant player in the AI race highlights the dynamic nature of technological competition between the U.S. and China.

While the immediate impact on data centres and technology may be limited, the long-term implications could be profound.

As AI continues to evolve, the ability to innovate cost-effectively and collaborate across borders will be key to driving progress and maintaining competitiveness in the global technology landscape.

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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’.

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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.

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Qualcomm intensifies competition with Intel and AMD and others as the company introduces its newest AI PC chip

New AI chip from Qualcomm

Qualcomm has introduced the Snapdragon X Plus 8-core processor, intensifying its venture into the AI PC market and challenging competitors like Intel and AMD

The U.S. semiconductor powerhouse announced that the Snapdragon X Plus 8-core targets PCs priced from $700, aiming to broaden its chip reach to additional devices.

Moreover, Qualcomm has enjoyed backing from Microsoft, which is incorporating Snapdragon processors in its Copilot+ PCs.

Qualcomm says the company is also working on mixed reality smart glasses with Samsung and Google.

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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?

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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.

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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.

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Microsoft’s AI system Recall can take screenshots

Copilot

The UK’s data protection authority, the Information Commissioner’s Office (ICO), is reportedly making inquiries into a new screenshot feature available from Microsoft.

This feature, known as Recall, is a component of the Copilot+ suite and aims to take encrypted snapshots of a user’s laptop screen at intervals, storing them on the device. The ICO is examining the feature to determine the privacy protections in place.

Recall is designed to enable users to search their computer usage history using natural language, effectively creating a type of photographic memory of their activity. Concerns have been voiced about the feature’s potential to become a ‘privacy nightmare’ due to its ability to capture sensitive information. Microsoft has clarified that Recall is a voluntary feature, giving users the choice over the snapshots it collects. The data is kept on the local device and is inaccessible to Microsoft or others without access to the device.

The ICO’s investigation aims to ensure that companies thoroughly evaluate and address any risks to individual rights and freedoms prior to launching new technologies. Microsoft has reiterated its dedication to privacy and security, noting that these principles were integral to the development of Recall. The company has also indicated that users can specify the snapshots collected by Recall and that Microsoft Edge’s private browsing mode is not included.

Awareness of software features and privacy settings is crucial for users, particularly regarding personal data handling. The ICO’s inquiries represent a move towards addressing privacy concerns and safeguarding user data.

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Microsoft announces new PCs with AI chips

AI art

Microsoft is promoting new computers equipped with advanced chips, engineered to operate the new artificial intelligence (AI) capabilities embedded in the Windows operating system.

On Monday 20th May 2024, Microsoft unveiled a Surface Laptop and a Surface Pro tablet, both featuring a Qualcomm chip capable of executing AI tasks both online and offline.

The new Microsoft Copilot+ PCs feature chips designed by ARM and are powered by Qualcomm’s Snapdragon X Elite and X Plus chips, which are also based on ARM architecture. These Snapdragon-powered PCs represent the initial series of devices under the Copilot+ PC brand, introducing over 20 models from various manufacturers, such as Acer.

The partnership between Microsoft, Qualcomm, and PC manufacturers is focused on providing superior processing and quick response times, with these ARM-based chips being integral to the new AI designs.

In addition, manufacturers like Lenovo, Dell, HP, Asus, Acer, and Samsung are launching AI-ready PCs featuring Qualcomm’s Snapdragon X Elite and X Plus processors. These processors offer extended battery life and compatibility with Microsoft’s Copilot AI chatbot.

Microsoft’s powerful AI vision – some tech information

Windows PCs designed for AI, known as Copilot+ PCs, are fitted with new, powerful chips capable of an astounding 40+ TOPS, ensuring all-day battery life and access to cutting-edge AI models.

Promoted as the fastest and most intelligent Windows PCs ever created, they boast features like Recall, Cocreator, and Live Captions, which can translate audio from over 40 languages into English.

These devices include sleek, lightweight, and elegantly designed models from Microsoft Surface and OEM partners such as Acer, ASUS, Dell, HP, Lenovo, and Samsung. Pre-orders are now open, with availability starting on June 18 and prices reportedly beginning at $999. This represents a major shift in the Windows platform, placing AI at the forefront of PC architecture.

This progress is a big part of Microsoft’s wider initiative to drive AI innovation onto devices, enhancing the AI capabilities that are already present in the cloud through Copilot.

This is a massive development in the deployment of AI to the masses.