Memory prices have skyrocketed in the last couple years as AI chips eat up all the production capacity of the small crop of vendors.

The cost of tokens has thrown into doubt the AI business model — as evidenced by what's being called the 'AI selloff' which has battered some AI-dependent businesses the last few days, especially memory chip makers.

The cost of tokens has thrown into doubt the AI business model — as evidenced by what's being called the 'AI selloff' which has battered some AI-dependent businesses the last few days, especially memory chip makers.

the Fable retraction exposed model dependency risk, Satya's thesis defined the learning loop, & Salesforce's $3.6B Fin acquisition priced the harness.

OpenAI and Anthropic May Be Rivals, but Investors Aren't Picking Sides

The ChatGPT-maker announced it has filed paperwork to go public, just a week after rival Anthropic took the same step.

SpaceX assessed the total market for that business as $22.7 trillion, compared to $2.4 trillion for AI infrastructure and just under $2 trillion for the company's space efforts.

Swift entry into the S&P 500 would have triggered $14 billion of passive fund buying for SpaceX, according to Bloomberg Intelligence. The investment research arm of Bloomberg also estimated that OpenAI could have gained more than $8 billion, and Anthropic could have netted $4.6 billion from similar passive buying sprees triggered by their S&P 500 entries.

After years of essentially being the only player in the category, the seven-year-old startup is accelerating its growth as tech giants enter the enterprise AI search market with rival products.

If Nvidia has cracked the code on bringing AI agents easily, safely, and usefully to the masses, it could — and should — be big.

if Nvidia has cracked the code on bringing AI agents easily, safely, and usefully to the masses, it could — and should — be big

Anthropic leads OpenAI in business adoption, according to Ramp.

When does access to agents able to negotiate on your behalf improve market efficiency and equitable outcomes? When does it not?

The price tag of the AI gold rush: $725 billion. Will it pay off?

Anthropic will also use incremental capacity for Claude in Amazon Bedrock. The agreement includes expansion of inference in Asia and Europe to better serve Claude's growing international customer base.

The Meta cuts are the inverse. When one person with the right AI tools can do the work of 10-to-15 people, the person most at risk isn't the one using the AI. It's the one whose job description overlaps with what AI now does by itself.

A free, good-enough product is enough to change market dynamics.

The risk of this strategy to the ecosystem is that it makes previously attractive categories no longer viable.

lack of a well-defined user agent role in AI that's backed up by transparent, public standards... leaves a gap – it makes it harder for a marketplace to form.

That matters because AI hype is dying down, and companies are shifting focus from buzzy pilots to deployment and integration, where cheaper and more customizable tools tend to win.

When models change every 42 days, buyers can't assemble a best-of-breed stack.

The interest comes as Anthropic's annual revenue run rate has surged to about $30 billion, driven by strong demand from enterprise customers using its AI tools for coding, cybersecurity, and automation.

The integration also connects to Upwork's AI agent Uma, which helps automate parts of the hiring and execution process once a project is underway.

While some experts have speculated that general models will win out in performance over specialized models—that scale and compute will beat curation—the success of these companies shows that the market is making a more nuanced bet.

Reddit, Shutterstock, and News Corp are making hundreds of millions a year licensing their high-quality data to companies training AI, and those contracts are growing about 20 percent annually, according to their quarterly filings.

A surprising number of people are now employed as model trainers, feeding their human expertise to automated systems.

Tech valuations have compressed from 40x to 20x, and we are back at levels last seen before the AI boom began.

Claude usage rose by over 40% amid increased attention but remains far behind ChatGPT

a strong premium perception can sustain prices 10 to 20 percent above direct competitors without materially increasing churn or creating friction in the purchasing process.

in the past year Huawei has overtaken Nvidia as the leading source of AI computing power in China, at least in terms of rated FLOP/s

now there's going to be even more AI music pouring 00:09:04 into platforms which saturated Market in an already oversaturated Market

We live in an age of paradox. Systems using artificial intelligence match or surpass human level performance in more and more domains, leveraging rapid advances in other technologies and driving soaring stock prices. Yet measured productivity growth has fallen in half over the past decade, and real income has stagnated since the late 1990s for a majority of Americans. Brynjolfsson, Rock, and Syverson describe four potential explanations for this clash of expectations and statistics: false hopes, mismeasurement, redistribution, and implementation lags. While a case can be made for each explanation, the researchers argue that lags are likely to be the biggest reason for paradox. The most impressive capabilities of AI, particularly those based on machine learning, have not yet diffused widely. More importantly, like other general purpose technologies, their full effects won't be realized until waves of complementary innovations are developed and implemented. The adjustment costs, organizational changes and new skills needed for successful AI can be modeled as a kind of intangible capital. A portion of the value of this intangible capital is already reflected in the market value of firms. However, most national statistics will fail to capture the full benefits of the new technologies and some may even have the wrong sign