Morale inside Meta has plunged to what insiders describe as some of the lowest levels in the company’s history, as the social media giant’s layoff, tied to an aggressive push into artificial intelligence, exacts a heavy human cost on its remaining workforce.

The frustration boiled over last month when Meta laid off approximately 8,000 employees, roughly 10% of its total headcount, in yet another round of sweeping cuts tied to the company’s frantic refocusing on AI. Those who kept their jobs now find themselves increasingly saddled with repetitive, low-level tasks to train and refine AI models, a grind that many say is draining what little enthusiasm remains.

According to Wired, in an internal memo sent to staff on Friday, CEO Mark Zuckerberg tried to rally the troops by announcing a companywide AI hackathon scheduled for July. The response was swift and brutal, exposing a deep disconnect between leadership’s vision and the day-to-day reality for employees still reeling from cuts.

“I’m literally preoccupied with keeping the lights on for my team,” one employee wrote in an internal message quoted by Wired. “I have no incentive to participate, let alone have the time to do so.”

Another added, “I’m not sure that this company supports a hackathon culture anymore. People are being asked to cover more work with less support while their colleagues get laid off.”

A third worker noted: “I’ve participated in previous hackathons, but this no longer feels like an option alongside pod sprints in my corner of the company.”

Zuckerberg’s additional gesture, offering employees access to permanent desks instead of the controversial “hot desking” system, only seemed to underscore how precarious many roles had become. The move, intended as a positive signal, landed as tone-deaf amid widespread anxiety about job security.

A Painful Transition with Limited Payoff So Far

Meta’s difficulties stem from the broader challenges facing Big Tech as it races to catch up in the generative AI era. Despite heavy investment, the company continues to struggle to produce standout models that match the pace set by rivals like OpenAI, Anthropic, and Google. Insiders say the pressure to deliver results is intensifying, but the immediate human cost is mounting faster than visible breakthroughs.

Andrew “Boz” Bosworth, Meta’s chief technology officer, was unusually candid during an internal “Tuesdays with Boz” meeting on June 2. According to four people familiar with the call, Bosworth described the current atmosphere as “maybe not the worst it’s ever been in 20 years here, but it’s probably up there” — and “probably one of the worst it’s ever been.”

The only period he recalled as worse was the 2018 Cambridge Analytica scandal, when revelations about the misuse of millions of Facebook users’ data for political targeting triggered a massive crisis of trust, regulatory scrutiny, and reputational damage. At the time, whistleblower Christopher Wylie exposed how the firm had harvested data to influence campaigns, including Donald Trump’s 2016 presidential run and the UK’s Brexit referendum.

Zuckerberg himself acknowledged the difficulties in his memo, admitting that the AI transition has been messy.

“Given the complexity of these changes, we’ve made mistakes and will almost certainly make more,” he was quoted as saying.

He pledged to avoid further layoffs for the rest of the year, but the damage to trust appears significant. Employees who survived previous rounds now face heavier workloads with fewer resources, fueling resentment toward a leadership team that continues to emphasize long-term AI bets over near-term stability.

The Big Tech’s AI Reckoning

Meta’s situation is not unique, but its scale and visibility make it a bellwether for the industry. Across Silicon Valley, companies are pouring tens of billions into AI infrastructure while simultaneously trimming headcount to improve efficiency. The result is a workforce that feels both essential to the future and expendable in the present.

For Meta specifically, the pivot carries extra weight. The company’s core advertising business still generates enormous cash flow, but growth has slowed as users fragment across platforms and regulators tighten oversight. AI is seen as the next growth engine, powering everything from content recommendation to ad targeting and new products, yet translating that vision into reality has proven slower and more painful than expected.

The hackathon misstep highlights a deeper cultural challenge. What once felt like an innovative, energizing part of Meta’s identity now strikes many as tone-deaf busywork when teams are stretched thin, and colleagues have just been shown the door.

Industry observers warn that sustained low morale could undermine Meta’s ability to attract and retain top talent at a time when competition for AI experts is fierce. If the best engineers and product minds start looking elsewhere, the company’s ambitious roadmap could slip further behind.

Zuckerberg’s memo and Bosworth’s comments are seen as a suggestion that leadership recognizes the gravity of the situation, even if their proposed remedies have so far fallen flat. As Meta bets its future on artificial intelligence, it is painfully discovering that keeping its human workforce engaged may be one of the hardest problems of all.

Intel shares surged in premarket trading Thursday after President Donald Trump announced that the chipmaker had reached an agreement with Apple to design and manufacture chips in the United States, a development that could mark a major turning point in the company’s years-long effort to regain relevance in the global semiconductor industry.

The stock climbed nearly 9% before the opening bell, extending a remarkable recovery that has transformed Intel from one of the market’s biggest laggards into one of its strongest-performing technology stocks. Over the past year, Intel shares have soared more than 460%, lifting the company’s market capitalization to approximately $609 billion.

Trump framed the agreement as part of a broader effort to rebuild America’s semiconductor manufacturing base and reduce dependence on Asia, particularly Taiwan, which remains the center of global advanced chip production.

“Apple has agreed to work with Intel to design and build its Chips in America,” Trump wrote on Truth Social.

The president also said that Nvidia had agreed to manufacture advanced chips through Intel’s foundry operations and said Elon Musk’s planned TerraFab facility would be developed in partnership with Intel’s technology teams.

Even so, the market reaction highlights how dramatically investor sentiment toward Intel has shifted over the past year.

For much of the previous decade, Intel was viewed as a symbol of missed opportunities in the semiconductor sector. The company lost technological leadership to Taiwan Semiconductor Manufacturing Company (TSMC), ceded market share in processors to Advanced Micro Devices (AMD), and largely missed the first wave of the artificial intelligence boom that propelled Nvidia into one of the world’s most valuable companies.

That narrative has changed significantly under Chief Executive Lip-Bu Tan.

Since taking over, Tan has focused aggressively on transforming Intel into a contract manufacturer capable of competing with TSMC, a strategy widely viewed as essential to restoring the company’s long-term growth prospects.

However, the importance of an Apple partnership goes far beyond the immediate revenue opportunity. The iphonemaker has historically relied heavily on TSMC to manufacture its custom-designed chips for iPhones, iPads, and Macs. Securing even a portion of Apple’s production would represent one of the strongest endorsements yet of Intel’s foundry ambitions. Such a move would also align closely with Washington’s broader push to localize semiconductor manufacturing amid escalating geopolitical tensions and supply-chain concerns.

The announcement emerges when artificial intelligence has transformed chipmaking from a cyclical technology business into a strategic national priority. Governments around the world increasingly view semiconductor production as critical infrastructure, while companies are spending hundreds of billions of dollars on AI-related hardware.

That spending has created enormous demand for advanced chips, data centers, and manufacturing capacity. Intel’s resurgence is therefore occurring against the backdrop of what many analysts describe as a new industrial arms race centered on AI.

Trump’s comments suggest that Intel may be evolving into a key beneficiary of that trend. The company has spent years investing tens of billions of dollars in new fabrication facilities across the United States, betting that governments and customers would eventually prioritize domestic production. For much of that period, investors questioned whether those investments would generate sufficient returns.

However, recent developments have begun to change that perception.

Nvidia’s reported manufacturing commitments, the potential Apple partnership, and the Trump administration’s public backing collectively strengthen Intel’s argument that its foundry strategy is gaining traction.

Industry analysts believe that if Apple shifts a meaningful portion of its chip manufacturing to the United States, it could accelerate broader efforts to diversify semiconductor supply chains away from Taiwan. That would represent one of the most consequential changes in the global technology industry in decades.

But Taiwan currently produces the overwhelming majority of the world’s most advanced semiconductors. Any disruption to production there, whether from military tensions or natural disasters, could have severe consequences for global technology markets.

Successive U.S. administrations have sought to reduce that dependence through subsidies, industrial policy, and incentives for domestic manufacturing.

Intel’s foundry expansion has become a centerpiece of that strategy.

The timing is also notable because the semiconductor sector remains one of the biggest winners from the AI investment boom.

While conflicts in the Middle East and broader economic uncertainty have weighed on parts of the market, AI-related stocks have continued to attract investor capital.

The Nasdaq PHLX Semiconductor Index has risen roughly 90% this year, reflecting expectations that AI infrastructure spending will remain elevated for years.

Investors increasingly view semiconductor manufacturers as the foundation of the AI economy, much as cloud providers became the backbone of the internet era.

For Intel, the challenge now shifts from attracting customers to executing on its promises.

Building cutting-edge chips for companies such as Apple and Nvidia requires manufacturing precision that rivals or exceeds TSMC’s capabilities. Any delays or technical setbacks could undermine confidence in the foundry strategy.

Still, the market’s reaction suggests investors believe Intel is closer than it has been in years to achieving a turnaround.

If the company successfully converts high-profile partnerships into long-term manufacturing contracts, Intel’s recovery could evolve from a stock-market comeback story into one of the most significant industrial revivals in modern American technology history.

More broadly, the developments underscore how the AI boom is reshaping the semiconductor landscape. What began as a race to build better AI models has become a competition to control the infrastructure that powers them, and Intel is positioning itself as a central player in that contest.

China’s artificial intelligence race has entered a new phase, one where access to elite engineers may be as valuable as access to capital.

Chinese AI startup DeepSeek reportedly attached an unusual condition to its first major external fundraising effort: investors must agree not to poach its employees or encourage them to launch competing ventures.

According to a report by fundraising-focused media outlet 36Kr cited by CNBC, founder Liang Wenfeng told prospective investors during a four-hour virtual fundraising meeting in May that any investment in the company would require a commitment not to recruit DeepSeek staff.

The condition is understood to be attached due to the growing fierce battle for AI talent in China, where technology giants and emerging startups are competing aggressively to secure researchers capable of building advanced artificial intelligence systems and, ultimately, artificial general intelligence (AGI).

The reported demand comes as DeepSeek concluded its first external funding round this week, raising $7.4 billion and securing a valuation exceeding $50 billion. The fundraising makes DeepSeek the most valuable pure-play AI startup in China.

The company’s willingness to seek outside capital marks a significant shift. Since its founding, DeepSeek had largely avoided external funding, preferring to focus on research and model development rather than commercial expansion. However, growing competition for talent appears to have altered that strategy.

The startup has already experienced notable departures.

Among the most significant was the exit of Luo Fuli, a key contributor to DeepSeek’s V3 large language model. Luo left the company late last year to lead MiMo, the AI model team at Xiaomi. Since then, Xiaomi’s AI models have reportedly outperformed some of DeepSeek’s offerings on selected industry benchmarks.

DeepSeek’s concerns are unfolding against a backdrop of intense competition among China’s largest technology companies.

Reports indicate that engineers and researchers are increasingly moving between major AI employers, often with lucrative compensation packages and access to larger computing resources. Earlier this year, ByteDance reportedly lost two prominent AI developers to Tencent. Meanwhile, The Information reported that Tencent invested $20 million in a new AI research laboratory established by Juyang Lin, the former lead researcher behind Alibaba Group’s Qwen models.

Lin announced in March that he was stepping down from the Qwen project, one of China’s leading large language model initiatives.

Alibaba itself has been navigating internal debates over AI strategy. Bloomberg reported in June that the company replaced the head of its enterprise-focused DingTalk platform following disagreements about the unit’s role within Alibaba’s broader AI ambitions.

Chinese firms are also looking beyond domestic talent pools.

Tencent hired Yao Shunyu from OpenAI last year, appointing him chief AI scientist. The move underscored a growing trend among Chinese technology companies to recruit researchers with experience at leading U.S. AI laboratories.

Both Liang and Yao have publicly argued that China should fully commit to pursuing AGI, generally defined as artificial intelligence capable of performing intellectual tasks at or beyond human levels across a wide range of domains.

For DeepSeek, protecting its workforce has become increasingly important as its profile rises globally.

The company burst onto the international AI scene early last year with models that challenged established Western competitors while operating at significantly lower reported training costs. That success elevated DeepSeek from a relatively obscure Chinese research lab into one of the industry’s most closely watched companies.

Its latest fundraising round provides substantial resources to expand computing infrastructure, recruit researchers, and accelerate model development. Yet the reported anti-poaching condition suggests DeepSeek views human capital, rather than funding, as the most critical resource in the next stage of the AI race.

The move also reflects a broader reality across the global AI sector: while billions of dollars continue to flow into model development, the pool of elite researchers capable of building frontier systems remains relatively small.

As competition intensifies between DeepSeek, Tencent, Alibaba, ByteDance, and other AI contenders, retaining those researchers may prove just as important as attracting new investors.