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Meta’s Talent Raid on OpenAI Intensifies Amid AI Arms Race – Hires Four More Researchers

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Meta’s aggressive hiring push to supercharge its artificial intelligence research has continued unabated, with The Information now reporting that four more researchers have jumped ship from OpenAI to join Mark Zuckerberg’s AI ambitions.

The latest hires — Shengjia Zhao, Jiahui Yu, Shuchao Bi, and Hongyu Ren — follow earlier reported departure of Trapit Bansal, a key contributor to OpenAI’s reasoning model o1, and three others: Lucas Beyer, Alexander Kolesnikov, and Xiaohua Zhai, according to The Wall Street Journal.

These moves mark a sharp escalation in Meta’s quiet but high-stakes war for elite AI talent. Zuckerberg has signaled that Meta’s future is tied to advancing “AI superintelligence,” with plans to embed powerful reasoning models into its consumer products and business tools.

Sources say Meta is offering eye-watering compensation packages, with some top researchers reportedly receiving offers valued at up to $100 million, though Meta’s CTO Andrew Bosworth downplayed the headline figures, saying the actual terms are “more complex.”

A Response to Llama 4’s Underperformance?

The hires come in the wake of April’s launch of Meta’s Llama 4 — a suite of open-weight AI models that, while widely used, reportedly failed to meet internal expectations. Zuckerberg had hoped the release would rival OpenAI’s GPT-4, Anthropic’s Claude, and Google’s Gemini in terms of performance and reasoning capability. Instead, it drew criticism for the model used in Meta’s benchmark testing, with some accusing the company of using a specialized version that didn’t reflect the real-world product.

These setbacks appear to have pushed Meta to redouble its efforts. The company’s AI superintelligence unit — which now includes former OpenAI, DeepMind, and GitHub talent — is being structured similarly to Google DeepMind, operating as a core engine to power future Meta products, including virtual assistants, business agents, and advanced developer tools.

OpenAI Pushes Back

OpenAI CEO Sam Altman, whose company has been under scrutiny from regulators and partners alike in recent months, has downplayed the poaching spree, saying “none of our best people have decided to take him up on that.” But the growing number of high-profile exits tells a more complicated story, especially with researchers involved in OpenAI’s core reasoning and reinforcement learning efforts now switching allegiance.

Tensions between the two companies have reportedly deepened. Meta is said to be courting AI startups for acquisitions or partnerships — including Scale AI, where former CEO Alexandr Wang is now part of Meta’s superintelligence team, and failed talks with Safe Superintelligence, Thinking Machines Lab, and Perplexity.

Why This Matters

AI talent is the new oil, and companies like Meta, OpenAI, Google, and Microsoft are locked in a battle to secure the best minds. Unlike traditional tech recruitment, these roles aren’t just about staffing — they determine who builds the next generation of frontier models.

Meta’s push into reasoning models aims to address a key performance gap. OpenAI, Google, and DeepSeek have all released advanced models that handle complex, multistep problem-solving tasks — and Meta wants to catch up quickly. The success of that effort could define the company’s long-term competitiveness in both the consumer and enterprise AI markets.

In the meantime, OpenAI is reportedly preparing to release a public-facing reasoning model in the coming weeks, which could raise the stakes even further for Meta and others racing to lead in this space.

However, the bottom line is that Meta is building an elite task force to challenge OpenAI and other leading AI companies at their strongest point — reasoning and autonomy.

Trump Halts All Trade Talks with Canada Over Digital Tax on U.S. Tech Giants

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President Donald Trump has abruptly ended all trade negotiations with Canada, escalating tensions between the two close allies after Ottawa moved forward with a digital services tax targeting large American technology firms.

In a fiery post on Truth Social Friday, Trump accused Canada of imposing a “direct and blatant attack on our country,” adding that the United States would “let Canada know the tariff that they will be paying to do business with the United States of America within the next seven day period.”

“We have just been informed that Canada, a very difficult Country to TRADE with… has just announced that they are putting a Digital Services Tax on our American Technology Companies,” Trump wrote. “They are obviously copying the European Union… Based on this egregious tax, we are hereby terminating ALL discussions on Trade with Canada, effective immediately.”

Trump later doubled down on his stance during comments in the Oval Office, saying the U.S. would “stop all negotiations with Canada right now until they straighten out their act.” He accused the Canadian government of being “foolish” for proceeding with the tax, warning, “We have such power over Canada.”

Canada’s Digital Services Tax

At the heart of the dispute is Canada’s Digital Services Tax (DST), passed last year but only now set to take effect, retroactive to 2022. The DST is aimed at large digital corporations generating revenue from Canadian users—most notably U.S. tech giants like Amazon, Google, and Meta.

Canada’s decision to proceed with the tax has stirred sharp criticism from Washington. Treasury Secretary Scott Bessent said Friday on CNBC that the retroactive component of the tax was “patently unfair” and warned that it would provoke further action from the Trump administration.

Bessent said U.S. Trade Representative Jamieson Greer is preparing to launch a Section 301 investigation, a powerful tool under U.S. trade law typically used to combat unfair foreign practices. A similar process was used during Trump’s first term to justify sweeping tariffs on Chinese imports.

The breakdown in talks places an enormous strain on one of America’s most important trading relationships. Canada and the United States traded over $762 billion in goods in 2023, according to USTR data. The countries, both part of the USMCA (United States-Mexico-Canada Agreement), had maintained relatively stable trade ties with each other until now, despite other disagreements in recent years.

Trump has long criticized Canada over agriculture tariffs, particularly its protectionist dairy sector, claiming U.S. farmers face unfair barriers. In his statement Friday, Trump revived those grievances, accusing Canada of imposing “as much as 400% tariffs” on American dairy products.

The Canadian government, led by Prime Minister Mark Carney, has not yet responded publicly to Trump’s declaration. Earlier this month, Canadian officials reaffirmed that they would not pause implementation of the digital services tax, despite fierce lobbying from Washington.

Political and Market Fallout

The announcement had immediate ripple effects on Wall Street. The S&P 500 and the Nasdaq Composite—which had both hit record highs earlier in the day—turned negative following Trump’s statement. Analysts say tech stocks in particular are sensitive to regulatory and tax policies in foreign markets.

Trump’s decision also comes amid mounting U.S.-EU tensions over similar digital tax policies. The EU has long pushed for tech firms to pay more taxes in the regions where they derive revenue, rather than where they are headquartered. The Trump administration views such moves as discriminatory and protectionist, with officials warning of broader trade retaliation.

In April, the European Union said it was “keeping all options on the table” if it failed to resolve tariff tensions with Trump, signaling that tech regulation may be used as leverage in broader trade disputes.

With trade talks off the table and tariffs looming, Washington is now preparing for a possible escalation. A Section 301 probe could result in punitive tariffs on Canadian exports, potentially impacting sectors like automotive, lumber, and agriculture—key pillars of Canada’s economy.

Microsoft Hit with Lawsuit over Pirated Books in AI Training—but Recent Court Wins Signal It Could Prevail

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Microsoft is facing a new lawsuit from a group of prominent authors who accuse the company of using pirated copies of their books to train its Megatron artificial intelligence model.

Filed Tuesday in a federal court in New York, the suit adds to a growing wave of legal challenges from writers, publishers, and news organizations accusing major AI developers of exploiting copyrighted material without consent.

The plaintiffs—who include American Prometheus author Kai Bird, essayist Jia Tolentino, and historian Daniel Okrent—allege that Microsoft trained Megatron using a dataset containing nearly 200,000 pirated books, without notifying or compensating the authors. According to the complaint, the AI model was engineered not just to learn the language but to mimic “the syntax, voice, and themes” of the authors’ works, enabling it to generate text that closely resembles their original expression.

“The Megatron model is not merely informed by our work,” the complaint says, “it is fundamentally built on it—without authorization and without compensation.”

The authors are seeking a court order to block Microsoft’s alleged infringement and statutory damages of up to $150,000 for each work, which could result in millions of dollars in liability if the court rules in their favor. Microsoft did not immediately respond to requests for comment, and the authors’ lawyer declined to speak on the case.

But while the lawsuit appears to be part of a broader campaign by copyright holders to rein in unchecked AI training, recent court rulings suggest Microsoft might actually have the upper hand.

In just the past week, two key decisions have tilted in favor of AI companies. In one, U.S. District Judge William Alsup ruled that Anthropic’s use of copyrighted books to train its Claude AI system fell under “fair use,” calling the process “exceedingly transformative.” Alsup held that training a model to understand and generate language based on large swaths of text was different in purpose from the original works, thereby satisfying one of the primary tests for fair use under U.S. copyright law.

A day earlier, Judge Vince Chhabria dismissed a similar case brought against Meta over its Llama model, stating flatly that “there’s no disputing” the transformative nature of what Meta had built. Chhabria also noted that the authors failed to show the AI system had caused meaningful harm to the market for their books, another key factor in determining fair use.

While neither ruling directly applies to the Microsoft case, legal analysts say the decisions could shape how judges evaluate similar claims moving forward. It is believed that both judges signaled that courts are leaning toward treating AI training as a transformative, fair use of copyrighted material—especially when the output doesn’t directly compete with or replace the original work.

The back-to-back rulings are being hailed as tentative but important victories for companies like Anthropic, Meta, OpenAI, and now, potentially Microsoft. However, the authors’ lawsuit takes a slightly different tack by emphasizing that the company allegedly used pirated copies of their books, which could complicate Microsoft’s defense even if training itself is deemed lawful.

The court may need to examine not just the legality of the AI’s purpose but also the nature of the data it was fed.

The situation underscores the complexities of copyright law in the AI age. Rather than offering clarity, the recent rulings have deepened the complexity of the issue. They suggest that while training on copyrighted material may, in many instances, qualify as fair use, there may still be legal consequences depending on how that material was acquired.

Now, Microsoft’s case has become another test of where the boundaries of fair use end and where infringement begins. Some analysts believe that this issue will require Congress’ or the Supreme Court’s intervention, or this evolving legal gray area is likely to remain unsettled.

Warren Buffett Donates $6bn in Berkshire Shares, Reinforces His Longstanding Philanthropic Pledge

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Warren Buffett, the legendary billionaire investor and chairman of Berkshire Hathaway, has announced a fresh charitable donation totaling $6 billion worth of Berkshire Hathaway Class B shares.

The move is the latest installment in Buffett’s nearly two-decade commitment to give away the bulk of his wealth, and it cements his place among the most prolific philanthropists in history.

In a statement released Friday, Buffett said he donated 12.4 million Class B shares to five philanthropic organizations, led by the Bill & Melinda Gates Foundation Trust, which will receive 9.4 million shares, worth approximately $4.6 billion.

The remainder of the shares were distributed among four family-linked charities: the Susan Thompson Buffett Foundation, the Sherwood Foundation, the Howard G. Buffett Foundation, and the NoVo Foundation, each receiving about 660,000 shares.

Buffett, now 94 years old, remains one of the wealthiest people on the planet, with a net worth of $152 billion, according to Bloomberg’s Billionaires Index. He first pledged in 2006 to donate the vast majority of his fortune to philanthropic causes and has since made annual contributions, steadily reducing his stake in Berkshire without ever selling shares for personal gain.

“When originally made, I owned 474,998 Berkshire A shares worth about $43 billion and those shares represented more than 98% of my net worth,” Buffett said. “During the following 19 years, I have neither bought nor sold any A or B shares nor do I intend to do so.”

Today, Buffett owns 198,117 Class A shares and 1,144 Class B shares, representing over 99% of his fortune. He emphasized that the value of the shares he has already donated — over $60 billion — exceeds his entire net worth when he first made the 2006 pledge.

Reflecting on his wealth, Buffett downplayed any sense of financial genius. “Nothing extraordinary has occurred at Berkshire,” he wrote, attributing his success to “a very long runway, simple and generally sound decisions, the American tailwind, and compounding effects.”

Philanthropy on a Grand Scale: Bill Gates and MacKenzie Scott

Buffett’s latest donation again elevates the Bill & Melinda Gates Foundation Trust, which has been a key beneficiary of his wealth since 2006. The Gates Foundation, co-founded by Microsoft co-founder Bill Gates and his then-wife Melinda French Gates, is one of the largest private foundations in the world. It focuses heavily on global health, poverty alleviation, education, and climate adaptation, with projects ranging from vaccine distribution in Africa to sanitation improvements in South Asia. As of 2023, the foundation had disbursed over $77 billion in grants since its inception.

Earlier this year, Gates announced a plan to give all his wealth out by 2060, with most going into charity work in Africa.

Another modern titan of philanthropy, MacKenzie Scott, the ex-wife of Amazon founder Jeff Bezos, has rapidly redefined charitable giving in recent years. After her 2019 divorce settlement, she committed to giving away the majority of her wealth and has since disbursed over $17 billion to more than 1,600 organizations. Scott’s strategy emphasizes no-strings-attached donations, trusting recipients to allocate funds based on their own judgment, often benefiting underfunded nonprofits in education, racial justice, women’s health, and rural development.

Buffett’s Legacy as a Giver

Buffett co-founded the Giving Pledge in 2010 alongside Bill Gates and Melinda French Gates, encouraging billionaires worldwide to commit to giving away most of their wealth. Despite his age, Buffett has continued to fulfill that pledge without pause.

His focus on slow, compounding generosity mirrors the investment principles that built Berkshire Hathaway into one of the world’s most valuable companies.

With this latest donation, Buffett not only reiterates his philanthropic vision but also signals to a new generation of billionaires that generosity, not accumulation, is the enduring mark of legacy.

Tesla Car Drives Self to Buyer, Marking Company’s First Fully Autonomous Vehicle Delivery

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In what could prove more consequential than its much-hyped robotaxi rollout, Tesla has announced the first-ever fully autonomous vehicle delivery, completing a drive from its Austin Gigafactory directly to a customer — without anyone inside the car or remotely piloting it.

A video posted by Tesla on X (formerly Twitter) shows a Model Y navigating a varied route across highways, suburban neighborhoods, and residential streets before pulling up outside a customer’s apartment complex.

Tesla CEO Elon Musk, who had previously teased a June 28 debut, confirmed Friday that the feat was achieved a day earlier.

“There were no people in the car at all and no remote operators in control at any point. FULLY autonomous!” Musk wrote. “To the best of our knowledge, this is the first fully autonomous drive with no people in the car or remotely operating the car on a public highway.”

The buyer named Jose responded to the post saying: “That was me! So excited to have been a part of this thank you! @elonmusk @Tesla.”

A First? Not Exactly

Despite Musk’s claims, Waymo has already been operating fully driverless cars — including on highways — for over a year. The Google-owned autonomous vehicle unit currently runs freeway operations in Phoenix, Los Angeles, and San Francisco, though its access is limited to employees. While Tesla’s latest move is a significant technical and symbolic achievement, it’s not the industry’s first instance of true driverless highway navigation.

Why This Matters More Than Robotaxis

The announcement comes amid growing skepticism about Tesla’s robotaxi initiative, which launched earlier this week with in-vehicle safety monitors. Despite heavy promotion, several early tests captured incidents of poor driving behavior: crossing into oncoming lanes, abrupt braking, and awkward interactions at intersections.

Tesla has so far deployed 10 to 20 robotaxis, all Model Y vehicles fitted with Full Self-Driving (FSD) beta software. Human safety operators sit in the passenger seat with a kill switch, highlighting the cautious and still-supervised nature of the service.

The fully autonomous delivery, however, did not involve a human monitor or remote supervisor, making it a more confident demonstration of Tesla’s FSD progress. That said, it also raises regulatory and safety questions, as Tesla’s system still lacks the redundancies seen in competitors like Waymo and Cruise.

Tesla continues to rely solely on vision-based AI, using just eight cameras with no radar, no lidar, and no secondary steering or braking systems. By contrast, Waymo’s AVs are equipped with:

  • 5 lidars
  • 6 radars
  • 29 cameras
  • Plus multiple layers of redundancy in braking, steering, and onboard computing

This difference in design philosophy has fueled a long-running debate in the autonomous vehicle community. Musk has long dismissed lidar as a “crutch,” while some believe that Tesla’s approach is inherently less safe, particularly in poor lighting or weather conditions. Even Musk’s own AI chatbot, Grok, reportedly acknowledged that adopting lidar could reduce phantom braking and improve FSD’s performance at night and during sun glare.

Where It Leaves Tesla

This delivery does show Tesla inching closer to its long-promised dream of unsupervised, city-to-city autonomy. But it’s still far from commercial viability on a large scale, particularly when contrasted with Waymo’s slow but methodical rollout of robotaxi fleets with verified safety data and state-level regulatory approval.

Tesla has not disclosed whether it will scale autonomous deliveries or under what conditions they may become common. Nor has it provided data on how many disengagements occurred during the route — a standard metric in the self-driving world used to evaluate safety and performance.

Ultimately, this may be less about immediate commercial deployment and more about reputation-building, especially as Tesla heads into its highly anticipated AI Day 2025 and tries to assure investors that its autonomous bets aren’t stalling.

While the milestone is important, Tesla still has a long road ahead before Full Self-Driving matches the safety records and regulatory acceptance.