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Take-Two CEO Says AI Can Build Game Assets, But Not the Next ‘Grand Theft Auto’

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Take-Two Interactive Chief Executive Officer Strauss Zelnick says artificial intelligence will reshape video-game production and improve efficiency across the industry, but he rejects the growing belief in Silicon Valley that AI alone can create the next blockbuster entertainment franchise.

Speaking on entrepreneur David Senra’s podcast, Zelnick said he is “all in” on AI as a productivity tool while arguing that the technology still lacks the originality, unpredictability, and cultural instinct required to produce a global hit comparable to Grand Theft Auto V.

“Remember what AI is, despite the fact that there are people in Silicon Valley who don’t want you to believe this,” Zelnick said. “It’s big data sets, lots of compute, and a large language model mushed together.”

“That’s what they are. So, data sets by their very nature are backward-looking.”

The comments offer one of the clearest views yet from a major gaming executive on how large publishers are approaching generative AI amid growing investor speculation that AI tools could radically lower development costs and disrupt traditional game studios.

Instead, Zelnick argued that AI is more likely to accelerate production workflows and asset generation than replace the human creativity behind successful entertainment franchises.

“AI so far is really great at asset creation, but hit creation isn’t asset creation,” he said.

‘Clones Don’t Sell’

Take-Two’s subsidiary Rockstar Games sits behind one of the most commercially successful entertainment franchises ever created.

Since its 2013 release, Grand Theft Auto V has sold more than 200 million copies globally, generating tens of billions of dollars across game sales, subscriptions, and online content.

Its successor, Grand Theft Auto VI, remains one of the most anticipated releases in modern entertainment after suffering multiple delays.

Zelnick acknowledged that AI systems may eventually generate games resembling existing titles but argued that imitation rarely creates lasting commercial success.

“AI could create another GTA lookalike,” he said. “But clones don’t sell.”

The remarks cut against mounting concerns across the gaming industry that generative AI could commoditize game development and erode the advantages held by established publishers. Technology companies and AI startups have increasingly promoted tools capable of generating game environments, dialogue, animation, coding, and visual assets using text prompts.

Some investors view those advances as a threat to large publishers whose development budgets for blockbuster games can exceed hundreds of millions of dollars.

Zelnick, however, argued that low barriers to entry have existed in gaming for years and have not eliminated the importance of creative execution.

“Anyone can make a video game last week,” he said. “Anyone could make a video game five years ago. The technology is readily available. It’s commoditized.”

What remains scarce, according to Zelnick, is the ability to create culturally resonant intellectual property that stands out in an oversaturated entertainment market.

AI Raises Creative Expectations Rather Than Cutting Costs

Zelnick’s position tags along a broader debate unfolding across Hollywood, gaming, publishing, and music over whether generative AI ultimately reduces labor demands or simply changes the type of work creators perform.

In a recent interview with Business Insider, Zelnick said Take-Two employees are already being encouraged to use AI systems such as Anthropic’s Claude and Google’s Gemini to assist with workflows and productivity. But he cautioned that technological efficiency historically tends to increase creative ambition rather than permanently lower development costs.

“Everyone understands this creates more work, not less work,” he said. “When you make certain things easier, your appetite gets greater.”

That observation mirrors patterns seen across previous technological shifts in entertainment and software development. As graphics engines improved, studios built larger and more detailed worlds. As internet speeds increased, games expanded into massive online ecosystems. As mobile hardware became more powerful, user expectations around visual quality and scale rose dramatically.

AI may now trigger a similar cycle.

Rather than replacing creative teams outright, industry executives increasingly expect AI to automate repetitive production tasks while pushing studios to pursue even larger, more sophisticated, and more immersive experiences.

That means a lot for Take-Two. The company is under enormous pressure to deliver another cultural phenomenon with Grand Theft Auto VI, especially as development timelines and budgets across AAA gaming continue to climb.

Industry analysts increasingly view blockbuster franchises as central pillars in the wider battle for consumer attention against streaming platforms, social media, creator economies, and AI-generated entertainment.

Zelnick’s comments suggest he believes the defining competitive advantage in that environment will remain human creativity, not merely computational power.

While AI may help developers build worlds faster, write code more efficiently, and generate assets at scale, he argues the technology still cannot replicate the originality and cultural intuition required to produce enduring global franchises. For publishers like Take-Two, that distinction could determine whether AI becomes a disruptive threat or simply another powerful tool in modern game development.

China Expected To Hold Lending Rates Steady As Liquidity Surge Offsets Pressure For Stimulus

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China is widely expected to leave its benchmark lending rates unchanged for a 12th straight month in May, signaling that policymakers are becoming increasingly cautious about deploying aggressive monetary easing even as economic momentum weakens and geopolitical tensions intensify.

A Reuters survey of 24 market participants showed unanimous expectations that the one-year loan prime rate (LPR) would remain at 3.00%, while the five-year LPR, the benchmark for mortgage pricing, would stay at 3.50% at Wednesday’s monthly fixing.

The anticipated pause underscores how the People’s Bank of China is attempting to balance slowing domestic growth against mounting inflationary risks tied to the ongoing U.S.-Israeli conflict with Iran and surging global commodity prices.

Although China’s economy continues to struggle with weak consumer demand, a prolonged property downturn, and sluggish private-sector borrowing, policymakers appear reluctant to cut rates further because financial conditions inside the banking system are already exceptionally loose.

Interbank cash levels have surged in recent weeks, reducing immediate pressure for additional easing.

The average overnight repo rate, a key gauge of liquidity in China’s banking system, has hovered near 1.2% over the past month, its lowest level since August 2023.

That means short-term market funding costs are already trading well below the PBOC’s official seven-day reverse repo rate, the main policy benchmark that anchors loan pricing across the economy.

Analysts at Huachuang Securities said the central bank therefore has “little incentive” to cut reserve requirement ratios or lower interest rates further.

The LPR itself is determined monthly after 20 commercial banks submit proposed lending rates to the National Interbank Funding Center, but the pricing mechanism is heavily influenced by the PBOC’s policy guidance.

The central bank last week reiterated its commitment to a “moderately loose” monetary stance. However, markets noticed a significant shift in tone.

Unlike previous quarterly policy reports, the latest implementation report omitted any direct references to possible cuts in interest rates or bank reserve requirements, reinforcing expectations that Beijing is entering a more measured phase of policy management.

That shift underlines growing concern inside China over imported inflation pressures stemming from the widening Middle East conflict. The war involving Iran has sharply lifted oil and commodity prices globally, increasing input costs for manufacturers and raising the risk that inflationary pressures could intensify further across Asia.

China’s producer prices unexpectedly accelerated to a 45-month high in April, while consumer inflation also picked up, complicating the PBOC’s room for maneuver.

The situation presents a difficult balancing act for Chinese policymakers, where, on one hand, economic activity continues losing momentum.

Industrial production slowed in April, while retail sales weakened to their lowest level in more than three years, highlighting persistent fragility in household spending and domestic confidence. Businesses also remain hesitant to borrow aggressively despite low financing costs, reflecting concerns over demand, margins, and broader economic uncertainty.

On the other hand, rising energy prices linked to geopolitical instability are beginning to create inflation risks that Beijing cannot entirely ignore.

Unlike Western central banks that spent the past two years battling entrenched inflation, China has largely faced the opposite problem: weak pricing power, subdued consumption, and deflationary pressure in several sectors.

But the Gulf conflict is now altering that equation.

Higher oil prices feed directly into transport, manufacturing, and logistics costs, increasing the likelihood of imported inflation even in economies with weak domestic demand. Still, most analysts believe the PBOC will maintain an accommodative bias overall, even without immediate rate cuts.

Ding Liang, an advisor to ?research firm Macro Hive, said the central bank remains focused on maintaining abundant liquidity to cushion the economy from external shocks tied to energy markets and slowing global growth.

Ding added that “weak credit demand and low bank funding costs are likely to keep long-term Chinese bond yields relatively contained.”

That dynamic increasingly distinguishes China from many advanced economies. While U.S. Treasury yields and global borrowing costs have climbed sharply amid inflation concerns and geopolitical risk, China’s bond market has remained comparatively stable.

Analysts attribute that resilience partly to China’s relatively closed financial system and its low correlation with international bond markets.

The stability also points to investor expectations that Beijing will avoid abrupt tightening even if inflation edges higher. The broader picture suggests Chinese policymakers are prioritizing financial stability over aggressive stimulus for now.

Authorities appear increasingly wary of reigniting leverage risks in property markets or creating excessive yuan weakness through large-scale easing measures. The yuan has already strengthened significantly this year due to robust exports and large trade surpluses, and the PBOC has repeatedly signaled discomfort with excessive currency volatility.

But Beijing is relying more heavily on targeted industrial support, infrastructure spending, and strategic investment programmes rather than broad monetary expansion to stabilize growth. That approach aligns with China’s longer-term effort to shift economic support toward advanced manufacturing, semiconductors, artificial intelligence, and energy security instead of debt-fueled property investment.

For global investors, the expected hold on lending rates supports the view that China’s stimulus cycle may remain restrained compared with previous downturns. The PBOC still has policy tools available if growth deteriorates further, but officials appear increasingly determined to avoid large-scale easing that could undermine financial stability or trigger capital outflows.

Much will now depend on how the Middle East conflict evolves. But Beijing appears content to keep liquidity abundant while holding benchmark lending rates steady, betting that targeted support and resilient exports can cushion the economy without resorting to aggressive monetary intervention.

Gold Prices Steady Near Recent Lows as Treasury Yields Ease Slightly Amid Sticky Inflation and Geopolitical Uncertainty

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Gold prices stabilized on Tuesday after hitting a one-and-a-half-month low the previous session, as traders weighed persistent inflation risks from the Middle East conflict against slightly softer U.S. Treasury yields and expectations for the Federal Reserve’s next moves.

Spot gold was down a modest 0.5% at $4,542.07 per ounce by mid-morning GMT. Prices had fallen to their lowest level since March 30 at $4,479.54 on Monday. U.S. gold futures for June delivery eased 0.3% to $4,545.50.

“Hawkish Federal Reserve expectations, driven by inflationary fears stemming from a protracted standoff in the Persian Gulf, are weighing on the precious metal,” said ActivTrades analyst Ricardo Evangelista.

Investors remain focused on developments between the U.S. and Iran. Any escalation or prolonged disruption in the Strait of Hormuz could keep energy prices elevated, reinforcing higher-for-longer interest rate expectations.

Yields Ease Modestly but Remain Elevated

Yields on U.S. Treasurys pulled back slightly early Tuesday, offering a brief reprieve after sharp rises the previous session. The benchmark 10-year U.S. Treasury note yield fell more than 1 basis point to 4.6073%. The longer-dated 30-year Treasury bond yield held steady at 5.1428%, while the 2-year note yield dropped more than 2 basis points to 4.0695%.

This came after yields had surged on Monday, with the 10-year note briefly touching its highest level in 15 months. A Bank of America survey released Tuesday revealed that 62% of global fund managers now expect 30-year Treasury yields to reach 6%, the highest level since late 1999, compared to just 20% who target 4%. Such a move would represent a significant increase of roughly 86 basis points from current levels and would further pressure non-yielding assets like gold.

Yields in Europe also remained elevated but eased modestly. Germany’s 10-year Bund yield dropped more than 1 basis point to 3.1471%, while the UK’s 10-year gilt yield stayed above 5% at 5.115%. Longer-dated debt showed similar pressure, with German 30-year bunds at 3.6836% and UK 30-year gilts at 5.773%.

Mohit Kumar, chief economist and strategist at Jefferies, highlighted the key drivers, saying: “Even if we get a [Middle East] deal… oil is not going back to pre-war levels. We think it’s going to be 25-30% higher in six months’ time.”

He noted that governments are likely to roll out fuel subsidies for households, which will increase borrowing and add upward pressure on the long end of the yield curve. However, Kumar cautioned against overinterpreting current market pricing.

“While the market is currently pricing in rate hikes, it’s not justified given that inflation is likely to rise as much as growth is likely to fall,” he said.

Oil Holds Firm Above Key Levels.

Brent crude was last seen 1.5% lower at $110.38 per barrel, while U.S. West Texas Intermediate held steady near $108.67. Despite the modest pullback, both benchmarks remain elevated, reflecting ongoing risks around the Strait of Hormuz and potential supply disruptions.

Outlook for Gold

Higher Treasury yields raise the opportunity cost of holding gold, which offers no yield. This dynamic has dominated price action recently, even as the metal retains its traditional safe-haven appeal amid geopolitical uncertainty. President Trump’s announcement on Monday that he had paused planned strikes on Iran after receiving a peace proposal provided some relief, but markets remain wary of a prolonged conflict.

Wednesday’s release of the Federal Reserve’s latest policy meeting minutes will be closely watched for clues on how policymakers view the balance between inflation risks and growth concerns.

However, gold’s performance reflects a classic tension: it benefits from geopolitical risk and inflation hedging properties, but suffers when those same forces drive real yields higher and strengthen the dollar. Analysts believe the current environment suggests gold may remain range-bound in the near term unless there is either a significant de-escalation in the Middle East or clearer signs that the Fed will look past near-term inflation pressures.

Longer-term investors continue to view gold as a critical diversifier in portfolios facing elevated geopolitical, inflationary, and fiscal risks. However, in the short term, the path of least resistance appears dictated by the interplay between energy markets, bond yields, and central bank signaling.

Mistral AI Buys Austria’s Emmi AI to Deepen Push Into Europe’s Industrial AI Race

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Mistral AI has acquired Austrian startup Emmi AI in a move aimed at expanding its industrial artificial intelligence capabilities and strengthening Europe’s effort to build homegrown AI systems for manufacturing, engineering, and advanced industrial automation.

The Paris-based AI company said Tuesday the acquisition of the Vienna-headquartered startup will enhance its ability to serve industrial clients across sectors, including semiconductors, aerospace, automotive production, and robotics.

Financial terms of the deal were not disclosed.

The transaction marks another sign that Europe’s AI ambitions are increasingly shifting beyond consumer chatbots and toward industrial applications, where European policymakers and companies believe the continent holds structural advantages because of its deep manufacturing base and engineering expertise.

Emmi AI specializes in physics-based AI models capable of simulating complex industrial processes involving airflow, heat transfer, pressure dynamics, and material stress. Such systems are becoming increasingly valuable as manufacturers attempt to integrate AI into factory automation, chipmaking, predictive maintenance, and industrial design.

The Austrian company raised 15 million euros earlier this year in what was described as Austria’s largest funding round of 2025.

The acquisition comes as the European Commission intensifies efforts to reduce Europe’s technological dependence on the United States and China in critical AI infrastructure. Last October, the Commission identified manufacturing as one of Europe’s “AI-critical” sectors under its broader industrial strategy aimed at strengthening regional technological sovereignty.

Unlike many U.S. AI firms focused heavily on large consumer-facing models, Mistral has increasingly concentrated on enterprise and industrial applications tailored to European corporations.

The company told Reuters the acquisition aligns with its strategy of building AI systems specifically designed around industrial workflows and operational environments rather than relying solely on general-purpose models trained on broad internet datasets.

Mistral said modern industrial deployments increasingly require multiple coordinated AI systems operating simultaneously inside factories and industrial infrastructure. One model may inspect products for defects using computer vision, another may control robotic equipment, while others process logistics, maintenance, or operational data.

By integrating Emmi AI’s physics simulation technology, Mistral believes those systems can interact more effectively with real-world industrial processes. The company said the acquisition will allow AI systems to simulate physical environments with greater precision, improving efficiency, reducing waste, and minimizing production downtime.

Mistral pointed to its existing collaboration with Dutch semiconductor equipment giant ASML as an example of industrial AI’s growing role in advanced manufacturing. According to the company, AI-powered vision systems embedded in ASML’s extreme ultraviolet lithography machines can now detect engraving defects significantly faster than traditional methods.

ASML CFO Roger Dassen told shareholders during the company’s April annual meeting that the technology reduced diagnostic times from hours to roughly eight minutes.

“You just save 10 hours of downtime on very expensive equipment,” Dassen said.

The efficiency gains are impactful in semiconductor manufacturing, where production interruptions can cost millions of dollars and defective silicon wafers create substantial financial losses.

The deal also marks a gradual shift to industrial AI. While consumer AI products such as chatbots have dominated public attention, industrial deployments are increasingly viewed as a potentially massive long-term revenue source because they directly affect factory productivity, logistics efficiency, and operational costs.

Mistral’s customer base already includes industrial and infrastructure companies such as Stellantis, Veolia, and defense-focused drone manufacturer Helsing. The company believes that highly specialized AI models trained on proprietary industrial data can outperform generalized AI systems built primarily for broad consumer usage.

That approach reflects a growing divide emerging inside the AI industry between companies pursuing giant universal models and those focusing on domain-specific systems optimized for sectors such as healthcare, manufacturing, finance, and defense.

CEO Arthur Mensch said the acquisition would strengthen Mistral’s role as an industrial technology partner across several strategic sectors.

The company said the addition of Emmi AI should deepen its capabilities in aerospace, automotive manufacturing, and semiconductor production, industries where Europe still maintains significant global industrial influence.

The acquisition is also seen as a further indication that Europe is taking its AI destiny into its hands in the global AI race. European leaders have grown concerned that the continent risks falling behind the United States in frontier AI model development while simultaneously becoming dependent on Chinese manufacturing capacity and American cloud infrastructure.

By focusing on industrial AI applications tied directly to Europe’s manufacturing strengths, companies like Mistral are believed to be attempting to carve out a competitive niche that differs from Silicon Valley’s consumer-centric AI race.

Blackstone Partners with Google in a $5 billion AI infrastructure venture powered by TPU chips

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Blackstone is deepening its bet on the artificial intelligence infrastructure boom with a new $5 billion partnership with Google, marking another episode of how the race for AI dominance is rapidly shifting beyond software models into ownership of the physical computing backbone powering the industry.

The new U.S.-based infrastructure company, announced Monday, will deploy Google’s proprietary tensor processing units, or TPUs, to build large-scale AI compute capacity, with the first 500 megawatts expected online by 2027 and plans for substantial future expansion.

The venture places Blackstone at the center of one of the fastest-growing segments of the global technology industry: AI data infrastructure.

As demand for generative AI systems accelerates, technology companies, cloud providers, and private equity firms are now scrambling to secure access to power, chips, networking capacity, and data centers capable of handling increasingly complex workloads.

“This new company has enormous potential as it helps to meet the unprecedented demand for compute,” Blackstone President and Chief Operating Officer Jon Gray said in a statement.

The deal also represents a major escalation in Google’s long-running effort to reduce dependence on Nvidia, whose graphics processing units have become the dominant hardware powering the global AI boom. While Google still uses Nvidia chips extensively across its cloud infrastructure, the company has spent years building its own semiconductor ecosystem around TPUs, chips specifically designed for artificial intelligence computations.

Unlike Nvidia’s GPUs, which are general-purpose accelerators originally developed for gaming and graphics rendering, Google markets TPUs as specialized processors optimized for machine learning and agentic AI workloads.

The infrastructure partnership, therefore, is seen as a reflection of more than a financing arrangement, as it signals Google’s attempt to establish its hardware architecture as a viable alternative to Nvidia’s near-monopoly in AI computing.

The rivalry has intensified as hyperscalers increasingly seek vertical integration to control both the software and hardware layers of AI systems. Amazon Web Services, for example, has developed its own Trainium and Inferentia chips, while Microsoft has expanded investment in proprietary AI processors through its Maia programme. Google was among the earliest major technology companies to pursue in-house AI chips, developing its first TPU as far back as 2015, years before the generative AI frenzy transformed semiconductor markets.

Now, the economics of AI are making that strategy increasingly important. The explosive growth of large language models has triggered an unprecedented surge in demand for computing infrastructure, driving shortages in high-performance chips, soaring data-center construction, and escalating electricity consumption globally.

Industry analysts increasingly describe compute capacity as the new bottleneck in AI. That has created massive opportunities for infrastructure-focused investors such as Blackstone, which has aggressively expanded across digital infrastructure, energy, and data centers in recent years.

The asset manager, which oversees more than $1.3 trillion in assets, is already the world’s largest private owner of data centers. Earlier this month, Blackstone launched another AI-focused infrastructure venture with Anthropic, highlighting how private capital is rapidly moving deeper into AI’s foundational layers rather than limiting exposure to software applications alone.

The latest partnership also underpins how Wall Street and Silicon Valley are teaming up in financing AI expansion. Building hyperscale AI infrastructure now requires enormous capital commitments that increasingly resemble utility or energy projects rather than traditional software businesses.

Training and operating advanced AI systems require massive amounts of electricity, cooling systems, networking hardware, and specialized semiconductor supply chains. The planned 500 megawatts of compute capacity in the Blackstone-Google venture would rank among the larger AI infrastructure deployments globally and reflects expectations that AI demand will continue growing sharply over the next decade.

The Wall Street Journal reported that the venture has already identified likely data-center sites, some of which are reportedly under construction. The company will be led by Benjamin Treynor Sloss, a longtime Google executive with deep operational experience in infrastructure scaling.

Neither Blackstone nor Google disclosed the ownership structure of the venture, although reports indicate Blackstone will hold a majority stake.

After years of dominating the AI hardware market, Nvidia is facing growing competitive pressure from customers determined to reduce dependence on a single supplier. This makes the partnership pivotal.

Nvidia’s extraordinary rise following the launch of OpenAI’s ChatGPT in 2022 transformed the chipmaker into the world’s most valuable company last year. But the company’s dominance has also created strategic concerns among hyperscalers wary of supply constraints, pricing power, and overreliance on one hardware ecosystem.

Google’s TPU strategy is partly aimed at solving those concerns internally while positioning its cloud business as an alternative AI infrastructure provider. The company already uses TPUs to run its Gemini AI models, while clients including Anthropic and Citadel Securities also use the technology.

The broader significance of the Blackstone-Google venture lies in how it highlights the next phase of the AI race. Competition is no longer centered solely on chatbots or consumer applications. Increasingly, the battle is about who controls the underlying infrastructure powering artificial intelligence itself. That includes semiconductors, energy access, cloud architecture, networking systems, and data-center capacity. In that environment, firms capable of controlling multiple layers of the AI stack may hold the strongest long-term advantage.

The market appeared to respond positively to the announcement, with shares of both Alphabet and Blackstone rising in premarket trading.