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Has Sora Become Too Huge a Liability for OpenAI? Disney Exits the $1 Billion Deal

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Sora
News

Has Sora Become Too Huge a Liability for OpenAI? Disney Exits the $1 Billion Deal

Has Sora Become Too Huge a Liability for OpenAI? Disney Exits the $1 Billion Deal

Was Sora’s computing demand that high for OpenAI to decide to shut it down? There’s more than what meets the eye.

It was merely a couple of months ago that OpenAI and Disney struck a three-year deal. The overall project centered on the use of Sora to create vertical video content, hinging on the AI startup’s access to over 250 Disney character licenses.

However, now that OpenAI is roping in Sora, just six months after it was made available to the public, Disney is also exiting the deal. And it wasn’t a small deal at that- while the AI organization was planning on maintaining access to hundreds of beloved characters, Disney was investing $1 billion to amplify this.

The truth is- Sora is a TikTok-like social feed. But it’s all AI.

So, there are two ways to keep users occupied on the platform: you create your own realistic deepfakes, or you use someone (or something) else’s. More users are, very rarely, willing to do the first.

Sora, with its impressive video generation qualities, witnessed an upheaval of deepfake videos that focused on real public figures or Disney characters. It was fun while it lasted. But public figures don’t hold the option to explicitly opt-in to being at the center of this- that’s where the problems begin. And entertainment ends up breaching personal boundaries.

Even with all the fantasy world characters, there wasn’t any explicit nod by Disney. Most thought OpenAI could end up in muddy waters with Disney, but obviously, that didn’t happen.

But Sora’s longevity was always in question.

AI slop has become ‘the’ reason for content fatigue- why would users specifically tap into an app that feeds them more of it?

Instagram reels or YouTube Shorts, and even TikTok- the OG vertical video feeds remain addictive because of the inherent “human” element they still entail. Not just the creators, even the actors are unapologetically human (but that’s also changing steadily).

That’s what Sora lacked. Because Sora 2, the video and audio generation tool, remains, it’s the AI-first social feed that’s shutting down. One doesn’t have to think too hard to gauge the reason- it’s a liability for OpenAI, an institution that’s losing money faster than it can count.

Microsoft
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Microsoft’s Data Center Rebound is a Lesson in High-Stakes Tech Real Estate

Microsoft’s Data Center Rebound is a Lesson in High-Stakes Tech Real Estate

Microsoft swoops in to lease a Texas data center dropped by Oracle and OpenAI. Here’s why this 700MW deal is a major power play in the AI infrastructure war.

The world of AI infrastructure often feels like a high-stakes game of musical chairs.

Recently, the music stopped for a massive data center project in Abilene, Texas, and while Oracle and OpenAI walked away, Microsoft was more than happy to take the seat.

That isn’t just a simple lease agreement.

It’s a 700-megawatt signal that the thirst for computing power is overriding the caution typically seen in such massive capital expenditures. The site sits right next to the famous “Stargate” campus, a project once heralded as the crown jewel of the Oracle-OpenAI partnership.

However, negotiations reportedly soured over financing hurdles and OpenAI’s shifting technical requirements.

For Microsoft, this is a pragmatic “trash to treasure” move.

Building these facilities from scratch takes years, but stepping into an existing developer agreement with Crusoe allows them to bypass the initial slog. It also highlights a growing rift in how the industry handles growth.

While some firms are tightening their belts due to high interest rates and the sheer cost of Nvidia’s latest chips, Microsoft seems content to double down, betting that there is no such thing as too much capacity.

Of course, this isn’t without risk.

Skeptics point out that the power grid in Texas is already under immense strain, and building the physical shells is only half the battle. Getting enough electricity to actually run 700 megawatts of AI hardware is a monumental task that could take until 2028 to fully realize.

This deal ultimately shows that scale is the only currency that matters in AI.

Microsoft is essentially betting that by the time this site is fully operational, the demand for generative AI will have caught up to the massive supply they are currently hoarding.

Google
News

The “North Star” Shift: Google’s Quiet Pivot to the Pentagon

The “North Star” Shift: Google’s Quiet Pivot to the Pentagon

Google DeepMind VP Tom Lue confirms the company is “leaning into” military contracts after scrubbing anti-weapons pledges from its 2025 AI principles.

For years, Google’s relationship with the military was a source of internal shame. The company effectively pinky-swore to avoid “weapons of war” after the 2018 Project Maven protests. But that era of Silicon Valley pacifism is officially over.

At a recent town hall, Google DeepMind VP Tom Lue dropped the pretense.

He reminded employees that the company’s AI principles were quietly updated in 2025, scrubbed of specific pledges against surveillance and weapons development. The new metric for taking a government contract is now remarkably flexible: whether the “benefits substantially exceed the risks.”

It isn’t just a change in wording; it is a change in the company’s soul.

While rivals like Anthropic are currently tied up in federal court for refusing to drop ethical “red lines” regarding autonomous weaponry, Google is leaning in. DeepMind CEO Demis Hassabis even noted he is “very comfortable”- working with democratic governments is a path to global safety.

The logic is simple.

The Pentagon is currently rolling out “Gemini for Government” to three million personnel, and Google wants a seat at that table. By framing the work as “administrative” or “clerical,” Google provides itself a layer of plausible deniability. Yet, the removal of the surveillance ban suggests the ceiling for this partnership is much higher than a glorified secretary.

Google’s “North Star” used to be its “Don’t Be Evil” manifesto.

Now, it mimics a calculated cost-benefit analysis. As the line between civilian tech and national security blurs, Google has decided that being a “supply chain risk” is a far greater danger to its bottom line than a few disgruntled employees.

Even TSMC is Hitting Its Capacity Limits- Something the Market Could Have Easily Defined as Infinite
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Even TSMC is Hitting Its Capacity Limits- Something the Market Could Have Easily Defined as Infinite

Even TSMC is Hitting Its Capacity Limits- Something the Market Could Have Easily Defined as Infinite

The AI boom is creating a domino effect. And with big tech locking up foundry capacities for at least 3 years, the lag seems permanent for the smaller players.

Reuters reports that even TSMC, the major producer of AI chips, is reaching its capacity limits with numerous supply chain constraints expected for the rest of the year. And honestly, the production limit isn’t about to increase any time soon, but a slight probability in 2027.

That will delay AI chip deliveries. But that’s a repercussion we all saw coming.

What’s more significant is how this scrunching of production capacity is impacting the rest of the market. Blame the boom in AI infrastructure because it’s not merely soaking up your memory but also your electricity flow.

In short, it’s resulting in a bottleneck migration- kind of a knock-off effect.

Suppliers are definitely prioritizing AI because of their billions of dollars worth of commitment to big tech companies. We’ve all seen it- the news headlines about the supercycle of huge investments by tech giants to ensure a constant supply of AI infrastructure and chips.

TSMC losing out on capacity isn’t a temporary demand swing. It’s that- the domino of bottlenecks.

The spearheaded focus on AI has pushed for an overwhelming demand for high-quality processors and memory. But then that pushed aside the common processors manufactured for consumer goods.

The traditional manufacturing capacity is sure to take the most brunt. You name it- packaging to raw material shortage, there’s a bunch of supplier constraints that aren’t even named. One of them is a warm shell shortage- it’s an expected crisis where AI firms have the chips but can’t power them. Hardware is sitting idle in warehouses in this case due to an electricity shortage.

As the demand for AI seems not to be taking a backseat, the problem will persist. It’s not a passing swing. It’s a structural imbalance, and TSMC’s production lapse just became the most crystal-clear proof of it.

AGI
News

Was All the Discussion on AGI Part of a Broader Industry Pattern? Jensen Huang Weighs In

Was All the Discussion on AGI Part of a Broader Industry Pattern? Jensen Huang Weighs In

Are we actually close to cracking AGI, or is that only a fantasy world that tech enthusiasts continue to expend billions into? Jensen Huang has an opinion.

NVIDIA’s CEO believes that they have “sort of” achieved AGI. You know, the tech dream- Artificial General Intelligence, AI that is on par with the human brain.

The claim.

It’s quite a recent but bold claim that Huang’s making. On the Lex Fridman Podcast, he states, “I think it’s now. I think we’ve achieved AGI,” in response to whether AI will finally come to match or surpass human-level intelligence.

Note: To offer readers context, Fridman frames AGI as an AI system capable of building and running a billion-dollar company.

However, what’s surprising isn’t the topic of AGI.

The “backtracking.”

It’s that Huang didn’t wait long before walking his claim back in the same conversation. He highlighted that Fridman was talking about running a $1 billion company, but he didn’t specify for how long. And with that, NVIDIA’s CEO elaborates that it’s not out of the question that someday Claude could create a web service or interesting app that a few billion people use briefly for $0.50 before it goes out of business.

He further comments, “A lot of people use it for a couple of months, and it kind of dies away,” saying the odds of AI agents “building NVIDIA is 0%.”

That sounds less like a backtrack and more like a sleight of hand. Because if AI can spin up, go through this entire cycle, and end up producing $1 billion in revenue even once? That reframes AGI, not as a durable future, but as a short-term commercial flash.

And that’s not what the tech leaders or investors thought AGI was ever about.

The market opinion and critics.

The opinions on AI aren’t in sync with the direction of the actual spending on AI infrastructure. Could it be that building a narrative around ‘imminent’ AGI will help justify all the ‘enthusiastic’ resource allocation? Well, all that depends on how you define imminent.

But all of this is also part of a well-known industry pattern. Huang called it a commercial flash; Altman says they’re very close to it, while Nadella disagrees that we could even imagine what AGI would be like at this point in time.

In short, Huang definitely agrees with Fridman’s narrow, commercially defined benchmark for AGI.

Maybe the chip leader realized mid-conversation that the current AI can’t sustain the kind of complex, stable institution that NVIDIA represents. So, how can we even assume we’re close to achieving AGI?

Meta
News

Meta Spent $80 Billion on a World Nobody Wanted to Live In. Now It Wants Your AI Budget.

Meta Spent $80 Billion on a World Nobody Wanted to Live In. Now It Wants Your AI Budget.

Meta scrapped its $80B metaverse bet and is pivoting to AI. Here’s everything Zuckerberg is asking you to trust him with next.

Mark Zuckerberg renamed his company after a virtual world in 2021- the Metaverse. This week, Meta confirmed it has stopped expanding that world. Horizon Worlds survives in reduced form. The Metaverse, as a strategic vision, does not.

The bill is $80 billion. That bought a virtual environment with roughly 200,000 monthly active users at its peak. A mid-size city newsletter outperforms that number.

The failure was not technical. Zuckerberg confused infrastructure ambition with human desire. People did not want legless avatar meetings. They wanted to call someone, share a photo, buy something. The platforms that won met people where they already were. The Metaverse asked them to relocate.

The people who built it deserve to be named separately from the decision that sent them there. Many believed in it genuinely. Some still do. They are not the story. The judgment that deployed them is.

Now Zuckerberg is pivoting to AI. The infrastructure investment is serious. The model work is competitive. The distribution across Facebook, Instagram, and WhatsApp is an advantage almost no one else holds.

He is asking the same public that watched $80 billion disappear to trust that this conviction is different. The reading on human behavior is better this time. That the room he is building is one people will actually want to enter.

He may be right. A track record, though, does not disappear because the next bet is more plausible. It sits on the table. It is sitting there now.