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The Lead At the Milken Institute Global Conference, leaders from across the AI supply chain gathered to discuss the current state and future of artificial intelligence. They touched on various challenges, including chip shortages, energy constraints, and the potential for new AI architectures. The Bottlenecks in AI Development The discussion highlighted several bottlenecks in AI development. Christophe Fouquet, CEO of ASML, noted that despite efforts to accelerate chip manufacturing, the market will likely remain supply-limited for the next two to five years. Francis deSouza, COO of Google Cloud, pointed out the immense demand for AI infrastructure, with Google Cloud's revenue growing 63% and its backlog nearly doubling to $460 billion. The Data and Energy Constraints Qasar Younis, co-founder and CEO of Applied Intuition, emphasized that the bottleneck for his company is not silicon but data gathered from the real world, which is essential for training physical AI models. The energy required to power AI infrastructure is also a significant concern. deSouza mentioned that Google is exploring data centers in space to address energy constraints, although this comes with its own set of challenges. New AI Architectures and Their Implications Eve Bodnia, founder of Logical Intelligence, discussed a different approach to AI, focusing on energy-based models (EBMs) that aim to understand the underlying rules of data, similar to human brain function. This approach could be particularly useful for applications requiring an understanding of physical rules, such as chip design and robotics. The Future of AI: Agents, Guardrails, and Trust Dmitry Shevelenko, chief business officer of Perplexity, talked about the evolution of its search product into a 'digital worker' called Perplexity Computer. This tool is designed to act as a staff that a knowledge worker can direct, raising questions about control and security. Shevelenko emphasized the importance of granularity in permissions and actions to ensure trust and security. The Geopolitical and Generational Impact The discussion also touched on the geopolitical implications of physical AI and its impact on national sovereignty. Younis noted that physical AI manifests in the real world in ways that governments can't ignore, leading to questions about safety, data collection, and control. Regarding the impact on the next generation, the panelists were optimistic, highlighting the potential for AI to help address significant problems and unleash new levels of creativity and opportunity.

The Unexpected Partnership On Wednesday, xAI and Anthropic announced a surprise partnership that has the Claude-maker buying out "all of the compute capacity at [xAI's] Colossus 1 data center," roughly 300MW that allowed Anthropic to immediately raise its usage limits. It's a huge deal for xAI, likely worth billions of dollars. More importantly, it immediately monetized one of the company's most impressive accomplishments, turning xAI from a consumer to a provider of compute. The Strategic Implications It's tempting to see the arrangement as a shot at OpenAI amid the ongoing lawsuit. But Musk's explanation on X was that xAI had already moved training to a newer data center, Colossus 2, and xAI simply didn't need them both. In the short term, there's an obvious logic at work. xAI's existing products are mostly focused on Grok, which has seen plummeting usage since the image generation debacles earlier this year. The Financial Impact xAI's partnership with Anthropic is likely worth billions of dollars. xAI was valued at $230 billion in its January funding round. CoreWeave, which oversees a comparable quantity of computing power, is worth less than a third of that. The Industry Context But beyond the short-term benefit, the Anthropic partnership sends an unusual message about where Elon Musk's priorities really lie. It suggests the company's real business may be more about building data centers than training AI models. It's rare to see a major tech company treat compute resources this way when companies like Google and Meta, which are also training models, are building more data centers. The Future Outlook By focusing on data centers (earthbound and otherwise), xAI is positioning itself more like a neocloud business: buying GPUs from Nvidia and renting them out to model developers like Anthropic. It's a far more difficult business, squeezed by both chip suppliers and the shifting cycles of demand. Musk's version of a neocloud is more ambitious, as you might expect. Some of the data centers might be in space — at least by 2035, if things go according to plan.

Apple's AI Strategy Shift Apple is set to revolutionize its iOS experience with the upcoming release of iOS 27, later this year. The new operating system will introduce a feature called 'Extensions,' allowing iPhone users to choose from a variety of third-party large language models to power different functions within the iPhone's operating system. The 'Extensions' Feature The 'Extensions' feature will enable users to access generative AI capabilities from installed apps on demand, through Apple Intelligence features such as Siri, Writing Tools, Image Playground, and more. This move is expected to be available not only for iOS 27 but also for iPadOS 27 and macOS 27. AI Model Options Models from Google and Anthropic are currently being tested. The status of ChatGPT, currently available to users, remains unclear but may continue as an option. The Impact of AI on Apple's Strategy Apple's approach to AI is centered around integrating AI capabilities into its existing hardware rather than investing heavily in building out AI infrastructure and services. This strategy comes as the company is perceived to be behind in the AI space compared to its peers. The Future Outlook With Tim Cook stepping down and John Ternus taking over, Apple is poised to make significant changes in its AI strategy. The company's ability to generate substantial AI-based revenue suggests that its focus on user-centric AI experiences could pay off in the long run.

Meta's Strategic Move into Humanoid RoboticsMeta announced the acquisition of Assured Robot Intelligence (ARI), a startup focused on foundation models that enable humanoid robots to understand, predict, and adapt to human behavior. The deal, made for an undisclosed sum, brings ARI’s co‑founders and research team into Meta’s Superintelligence Labs research division.Acquisition Details and Team IntegrationThe integration will see ARI’s leadership—co‑founders Xiaolong Wang and Lerrel Pinto—join Meta’s AI unit. Wang, a former Nvidia researcher and UC San Diego associate professor, and Pinto, a former NYU professor and co‑founder of Fauna Robotics (acquired by Amazon), both hold multiple prestigious awards.Acquisition price: undisclosedPrevious funding: undisclosed seed round from AIX VenturesTeam focus: foundation models for whole‑body humanoid control and self‑learningFinancial Forecasts and Market Size ProjectionsIndustry analysts remain divided on the long‑term value of humanoid robotics:$38 billion market estimate by 2035 (Goldman Sachs)$5 trillion market estimate by 2050 (Morgan Stanley)These figures illustrate both the massive upside and the uncertainty surrounding a technology still in its early commercial phase.Implications for the AI and Robotics LandscapeBy absorbing ARI, Meta gains:Deep expertise in robot‑centric model training, a pathway many experts see as essential for achieving artificial general intelligence (AGI).Accelerated development of consumer‑grade humanoid platforms, complementing Meta’s existing research on AI models and hardware.A competitive edge over rivals such as Amazon, Google, and Tesla, all of which are racing to embed AI in physical agents.Even if Meta ultimately opts not to ship a consumer robot, the acquisition signals a firm commitment to the research frontier where AI learns through embodied interaction rather than static data.Future Outlook: From Lab Prototypes to Consumer HumanoidsAnalysts anticipate a multi‑year timeline before any Meta‑branded humanoid reaches the market. Short‑term milestones include:2026‑2027: Integration of ARI’s models into Meta’s internal simulation pipelines.2028‑2029: Prototype demonstrations of household‑task robots for internal testing.Early 2030s: Potential pilot programs with select partners or developers.Success will hinge on breakthroughs in whole‑body control, energy efficiency, and safe human‑robot interaction—areas where ARI’s award‑winning team is already positioned to lead.

The Pentagon's AI Partnerships The Pentagon said on Friday it had reached agreements with seven leading artificial intelligence (AI) companies: SpaceX, OpenAI, Google, Nvidia, Reflection, Microsoft and Amazon Web Services. The Scope of the Agreements “These agreements accelerate the transformation toward establishing the United States military as an AI-first fighting force and will strengthen our warfighters’ ability to maintain decision superiority across all domains of warfare,” the Pentagon said in a statement. The Companies Involved SpaceX OpenAI Google Nvidia Reflection Microsoft Amazon Web Services The Impact on AI Development The US Department of Defense is budgeting tens of billions of dollars for numerous technology firms’ cutting edge programs related to intelligence, drone warfare, classified and unclassified information networks and much more. It has requested $54bn for the development of autonomous weapons alone. The Controversy Surrounding Anthropic Anthropic, which makes the popular Claude chatbot, had rejected including the lawful use standard in its contract with the Defense Department in a high-profile feud with the bureau last month. The Pentagon labeled Anthropic a supply-chain risk last month, the first time an American company has been designated as such. The Future of AI in the Military Defense department officials believe signing with Anthropic’s rivals could bring the holdout startup back to the negotiating table. Anthropic’s latest AI model, the cybersecurity-focused Mythos, has rattled government officials and bankers over its ability to find vulnerabilities in well-tested software.

The Pentagon's AI Integration Strategy Washington, DC – The United States Department of Defense has announced a new agreement with seven Artificial Intelligence companies to use their advanced technologies for its classified networks. This initiative represents a significant acceleration in the Pentagon's decade-long effort to integrate AI into military operations, aiming to establish the United States military as an "AI-first fighting force" capable of maintaining decision superiority across all domains of warfare. Key Players in the Defense AI Ecosystem The Pentagon's agreements include partnerships with SpaceX, OpenAI, Google, NVIDIA, Reflection, Microsoft, and Amazon Web Services. These companies will provide their AI capabilities for the military's most secure information systems to "streamline data synthesis, elevate situational understanding and augment warfighter decision-making in complex operational environments." Notably absent from the Pentagon's list is Anthropic, which had a major fallout with the Pentagon after pushing back on pressure to provide unrestricted access to its Claude AI programme for "all lawful use." The appeal raised concerns over Claude's possible uses in government mass surveillance and autonomous weapons systems, leading the Pentagon to label the company a "supply chain risk." The Pentagon's agreements with OpenAI and Google had previously been confirmed, as had a deal with Elon Musk's xAI. The three companies had agreed to the Pentagon's "all lawful use" provision as part of those agreements. Operational Scale of Military AI Implementation In its statement, the Pentagon revealed that over 1.3 million department personnel use its official AI platform, GenAI.mil. "Warfighters, civilians and contractors are putting these capabilities to practical use right now, cutting many tasks from months to days," the department stated. The Pentagon also emphasized its commitment to avoiding "vendor lock," a term for over-reliance on one vendor, by continuing to build the department's AI architecture with multiple partners. Geopolitical Implications of AI-Enhanced Defense The announcement comes amid wider scrutiny over involvement by companies with the US military, which has gained renewed attention amid a public fallout with the AI company Anthropic and questions over how AI has been used in the US-Israeli war with Iran. The US government's use of AI has gained increasing scrutiny amid its mass deportation campaign, with rights groups saying the technology company Palantir has been used to collect real-time data on potential Immigration and Customs Enforcement (ICE) targets, including pro-Palestine advocates. Amid the US-Israel war in Iran, questions have been raised over how AI targeting systems are being used. The Pentagon has said it has hit 13,000 targets since beginning attacks on February 28. At least 3,375 people have been killed in Iran, including at least 170 people, mostly children, in an apparent US Tomahawk strike on a girls' school in Minab. The Pentagon has said it is still investigating. Speaking during a Senate committee hearing on Thursday, US Senator Kirsten Gillibrand questioned Secretary of Defense Pete Hegseth on civilian harm oversight and the use of AI. Hegseth responded that "no military, no country works harder at every echelon to ensure they protect civilian lives than the United States military, and that is an ironclad commitment that we make, no matter how…no matter what system we use." The Future Trajectory of Military-AI Partnerships There has been an increasing desire from the administration to access Anthropic's powerful new Mythos AI model, which is seen as a potentially transformative tool in both cyber attacks and cyber defense. Despite the current legal battles, this suggests that the Pentagon may continue to pursue partnerships with Anthropic in specific domains where its technology offers unique advantages. The Pentagon's multi-vendor approach indicates a recognition of the strategic importance of diverse AI capabilities in modern warfare. As AI technologies continue to evolve at a rapid pace, we can expect to see even deeper integration of commercial AI solutions into military operations, accompanied by ongoing debates about ethical boundaries, civilian protection, and the appropriate limits of autonomous systems in warfare.

The Unexpected Surge in Mac Sales Apple's recent quarter saw iPhone sales and Services revenue take center stage, but the Mac segment quietly outperformed expectations. The tech giant reported $8.4 billion in Mac revenue for Q2, ended March 28, beating Wall Street's estimate of $8 billion. AI-Driven Demand Mac sales were up 6% year-over-year, defying expectations of flat growth. CEO Tim Cook attributed the growth to customers using Macs for local AI models, such as OpenClaw. The Mac mini and Mac Studio devices sold out in recent weeks, contributing to the surprise demand. The Role of New Product Launches Apple's recent product launches, including the MacBook Neo, played a significant role in the Mac sales growth. Cook described customer demand for the Neo as "off the charts" and higher than expected. Enterprise Demand and Market Trends Enterprise demand for Macs was a contributing factor, with companies like Perplexity turning to Macs for building AI assistants. The Mac mini was the top-selling desktop in China, a market experiencing high demand for AI-related products. School systems, such as Kansas City Public Schools, are also adopting Macs, with some dropping Chromebooks for the MacBook Neo. The Future Outlook Despite the strong demand, Mac revenue was flat on a quarter-over-quarter basis. Cook warned that it may take Apple "several months" to reach supply-demand balance on the Mac mini and Studio models.

In a Thursday post on X, Sam Altman confirmed that OpenAI will begin a controlled release of its GPT‑5.5‑powered cybersecurity suite, Cyber, to “critical cyber defenders” after publicly criticizing Anthropic for limiting access to its own tool, Mythos. OpenAI Mirrors Anthropic’s Gatekeeping with Cyber The announcement marks a clear shift from OpenAI’s earlier open‑access stance on its AI models. By restricting Cyber, the company aligns itself with Anthropic’s approach, positioning the limitation as a responsible safeguard against misuse. Application Process and Core Capabilities Prospective users must submit a detailed application outlining credentials, organizational role, and intended use cases. Cyber is designed for penetration testing, vulnerability identification (including exploitation), and malware reverse engineering. The toolkit aims to help enterprises discover security gaps and validate defenses before adversaries can exploit them. Security Community Reactions and Market Implications Industry observers see the move as both a protective measure and a competitive signal. While some praise the caution, others worry that limiting access could slow broader adoption of AI‑enhanced security solutions and give rivals a strategic edge. What’s Next for AI‑Powered Cyber Tools? OpenAI has indicated plans to broaden Cyber’s availability after consulting with U.S. government agencies and verifying user legitimacy. The trajectory suggests a phased expansion, with potential policy frameworks shaping how AI security tools are deployed across the sector.

Lead: Musk’s courtroom confession on AI distillationElon Musk told a federal judge that xAI had used distillation techniques on OpenAI models to help train its new chatbot Grok. The partial "yes" came during a high‑stakes lawsuit accusing OpenAI founders of betraying the nonprofit mission that originally guided the company.Musk’s courtroom admission on AI distillation practicesDuring Thursday's testimony, the judge asked whether xAI had employed systematic querying of OpenAI’s publicly available APIs to extract model behavior. Musk answered that such "distillation" is a "general practice among AI companies" and qualified his response with "Partly." The exchange underscores that the once‑rumored practice is now openly acknowledged in a legal setting.Distillation: prompting a model repeatedly to infer its internal weights and replicate its capabilities.Legal context: Musk is suing OpenAI, CEO Sam Altman, and co‑founder Greg Brockman for allegedly abandoning the nonprofit charter.Scale and rankings of AI playersWhile xAI remains a relatively small outfit—"just a few hundred employees"—Musk positioned it among the world’s top AI providers:1️⃣ Anthropic (ranked top by Musk)2️⃣ OpenAI3️⃣ Google4️⃣ Chinese open‑source modelsFounded in 2023, xAI’s rapid ascent to a contender in the market illustrates how distillation can accelerate capability development without the massive compute investments of larger rivals.Distillation’s threat to incumbents and industry responseThe practice erodes the advantage built by firms that have poured billions into custom silicon and data pipelines. By extracting knowledge from existing models, smaller labs can produce near‑equivalent performance at a fraction of the cost. In response, leading labs—including OpenAI, Anthropic, and Google—have launched a collaborative effort through the Frontier Model Forum to share defensive tactics, such as rate‑limiting suspicious query patterns and tightening terms of service.Future outlook: legal battles and the evolution of model trainingWith Musk’s admission on the record, the lawsuit may set precedents for how intellectual property and service‑agreement violations are judged in the AI space. Expect tighter API usage policies, increased monitoring of query volumes, and possibly new regulatory guidance on model‑copying techniques. Meanwhile, firms that can master distillation without breaching contracts could reshape the competitive landscape, forcing incumbents to innovate beyond sheer compute power.