As Anthropic suspends access to new models, India debates its AI future

tech

As Anthropic suspends access to new models, India debates its AI future

Tech leaders debate whether the Anthropic episode is a wake-up call for India’s AI ambitions.

TL;DR

Anthropic has suspended access to its new AI models (Fable 5 and Mythos 5) for foreign nationals due to a U.S. government directive.
This decision has reignited debate in India about its reliance on foreign AI technologies and the need for domestic capabilities.
Indian tech leaders are discussing whether to accelerate domestic AI development, invest in open-source alternatives, or continue depending on U.S. frontier model providers.
The episode highlights concerns about technological dependence, geopolitical influences on AI access, and potential competitive disadvantages for Indian startups.
Proposals include increased government investment in AI, computing infrastructure, and deep technology, with some suggesting a national mission and substantial funding.
India is a significant market for frontier AI companies like Anthropic and OpenAI, but remains a relatively small player in frontier model development.
The debate extends to how AI advancements might reshape global technology work and impact India's role as an engineering talent hub.

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Yann LeCun reposted

Naveen Rao

My team loves Claude from @AnthropicAI . But this new policy of retaining prompts and usage is a red line...we simply can't give over our usage. Prompts contain our IP; literally all our design files and docs. Why would this ever have been ok?

It's sad because everyone was looking forward to using the new model. Sigh.

Yann LeCun reposted

Daniel Jeffries

This ugly reality is staring us right in the face:

Americans will have walled AI gardens where we beg for access from a few East India companies, open source will get banned on national security grounds, and 6 billion people who aren't American, aka the rest of the world, will standardized on a Chinese AI stack.

Bloated. Broken. Slow. Ugly.

There's still time to change it but it's slipping through our fingers like fast running sand.

Read this passage below from Bill Gurley because it's about to become our hideous reality if we don't change course quickly.

"If a credible Western open frontier player does not emerge, the consequences cascade quickly.

This is the inverse of the early Internet wave. In the 2000s and 2010s, Western companies — Google, Facebook, Amazon, Apple, Microsoft — dominated globally while China carved out its own walled garden. The AI version flips that dynamic on its head. Without a credible Western open frontier player, the only open models capable of running entire economies are made in China. If U.S. policy further restricts Chinese open-weight access on national-security grounds, the U.S. ends up with two or three closed Cathedrals serving the U.S. market — and the rest of the world picks the AI stack that is free, capable, self-hostable, and not embargoed. Europe, Africa, Southeast Asia, Latin America, India, the Middle East. Roughly six billion people. Chinese open models become the global default by 2030, and the United States ends up technologically isolated from the majority of the world’s AI users. We would have done it to ourselves."

Fully essay in replies.

clem 🤗 reposted

Harry Stebbings

“We have a crisis of open source models in the Western world.

Outside of China, there are no good open source models. We don't even have any in the US now.

The talent, the capital and the focus to be best-in-class at pre-training, mid-training, post-training is an extremely scarce skillset.

The answer for a lot of countries may just be to take an open weights model from China, post-train or fine-tune their own version, and have that be what they start from." @EverettRandle

Why does the West have such poor open source models and is it a national security threat to rely on open-source Chinese models @demishassabis @ylecun @aidangomez @lilianweng @janleike

Yann LeCun reposted

Christopher Nguyen ⽗

Honored to welcome @iitbombay and BharatGen as founding contributors to Project Tapestry. India isn’t just adopting open & frontier AI — it’s helping build it, in its own languages and on its own terms. Sovereign by architecture, advanced together.

Cc @ylecun @FerrettiAgata @thealliance_ai

clem 🤗 reposted

MTS

SITUATION EXPLAINED: The frontier lab regulatory problem.

@ClementDelangue, co-founder and CEO of @huggingface:

"The frontier labs were basically doing marketing for the past few years. If you remember, GPT-2 was too dangerous to release. What, like four or five years ago. So I can't really blame them for doing things like that."

"I just hope that progressively we'll get a little bit more transparency about what is safe, not safe... more focus on transparent evaluation of models."

"I hope it's gonna stay contained to frontier generalist models and not permeate to a lot of different players... startups, small companies, academia, people who don't necessarily have the money, the size, the ability to really deal with these things."

clem 🤗 reposted

MTS

SITUATION EXPLAINED: What is at stake in the open source AI race?

We asked @perrymetzger, chairman of Alliance for the Future.

"Open source models are a sort of cultural ambassador and civilizational ambassador."

"If everyone ends up using Chinese open source models, it means that the answers that they get to their questions and the way that their software is and is not willing to behave ends up being dictated by the Chinese."

"It would be better from my point of view if the US was putting out a steady stream of open source AI models that were getting as much traction."

"It used to be that a number of these labs put out open source models regularly. Whisper, one of the early pioneering voice recognition models, came from OpenAI. Google still does open source with Gemma. But that's about it, it's like the only frontier lab that still does open source in America."

clem 🤗 reposted

The Information

Open source AI is gaining traction due to the White House’s clampdown on Anthropic & OpenAI.

“A lot of founders and developers have been burned by trying to build apps on top of these really advanced closed source models, like Fable for instance…”

“… and then seeing those models get taken down or removed from the market just days later.” — @steph_palazzolo, AI Reporter

Yann LeCun reposted

Adam Thierer

We stand at a critical crossroads in the debate over AI governance in the United States, and it feels like we are inching closer to a very serious battle over whether or not open source models will even be allowed in an environment where a new de facto licensing regime has been taking shape.

Lacking formal congressional statutory frameworks or clear administration rules (like the diffusion rule revision), we appear to be left with a sporadic, arbitrary, non-transparent process for model review. The fiction of “voluntary” agreements hangs over this debate, and some large model developers are already showing an incredible willingness to bend over backwards to accommodate national security-related officials / orders that the rest of us are not privy to. It's a very opaque process. And those model developers are expected to play ball with those officials, or else their models get pulled from the market or held up for long periods. Or they will lose any government procurement contracts they have. There is nothing “voluntary” about it when that Sword of Damocles hangs in the room.

As this mess worsens, at some point the question of how to handle open source models will come into sharper focus because it will have to. I've even heard some rumors lately that something may be coming from the admin on this front to address this.

Needless to say, if this informal new AI model review regime expands and takes on more pre-vetting characteristics / requirements, it is hard to see how open source players could comply with such quasi-licensing of AI models. Specifically, if this ambiguous new regime is accompanied by a general presumption of ‘restrict-until-permitted,’ then that would spell doom for open source. That is a very dark path for our country.

Worse yet, of course, would be a move by national security officials to more directly restrict open source models and capabilities. If that happens, then we would be right back in the thick of a Clipper Chip-like battle along the lines of what we saw in the late 1990s. That is a much darker path for America.

Meanwhile, open source developers have no “golden shares” or other goodies to offer the government to make their problems go away.

Let’s be clear: If our government takes the dark path, it will become the single most important battle over computational freedom of modern times. It is time for people to make a stand in defense of open source before it is too late.

Aravind Srinivas reposted

Chamath Palihapitiya

From Anthropic’s Fable model on the economic, moral, ethical and legal opinion of distillation of Anthropic’s Fable model:

Whether it’s a moral problem is genuinely contested. The labs trained their models on the open internet — copyrighted books, articles, code — largely without permission, and their fair-use defense is essentially “learning from data is transformative.” Distillation is the same argument turned against them: a model learning from another model’s outputs. It’s hard to construct a moral principle that permits the first and forbids the second, which is why critics call the labs’ objections hypocritical rather than principled.

Distillation is contentious because it lets a smaller model absorb much of a frontier model’s capability by training on its outputs — effectively free-riding on billions of dollars of compute, data curation, and RLHF work.

The DeepSeek episode made this concrete: if you can extract 80% of the value of a $1B training run for $5M by querying the API, the economics of frontier labs get shaky.

That’s the core anxiety — it’s a moat problem before it’s anything else.

Legally, it’s mostly a contract issue, not a copyright one. Model outputs likely aren’t copyrightable (no human author), so the labs’ real weapon is terms of service — every major API prohibits using outputs to train competing models. But ToS violations are breach of contract, hard to detect, hard to prove, and nearly unenforceable against a foreign entity. There’s no statute against distillation itself. So the practical answer: it’s an economic problem dressed in legal clothing, with a moral argument that cuts both ways depending on whose training data you start counting from.

David Sacks reposted

MTS

Sriram Krishnan reveals why it's easier to defend American code with a Chinese model than an American one right now:

"I don't think it is great that the leading open weight models or open source models are not American. There's some great innovation happening with Moonshot and with DeepSeek and with Qwen, but I would much rather prefer that the leading models are American."

"Linus Torvalds of Linux fame had a law that given enough eyes, all bugs are shallow. Open weight models are inherently secure because when you download a model off Hugging Face, the entire world can take it apart, inspect it, fine-tune it, look at it in ways that you absolutely cannot if they are closed."

"There was an incident with Hugging Face that got reported on earlier today. Hugging Face seems to have found that somebody was using an AI LLM agent to hammer them at multiple places and to find ways to break in."

"The way to counter that is to make sure American or Western or allies defenders have access to the best models to make our software just more secure."

"It may be harder to look at your own code for exploits with Fable than it is when you use a Chinese model. That's just like a weird spot to be, and I think we should fix that."

@sriramk

David Sacks reposted

Compound248 💰

Sacks drops an absolute bar, criticizing Anthropic for using “distillation” as a door to regulatory capture

“If stopping distillation was its primary objective, Anthropic would push to stop Chinese access to American models, not American access to Chinese models.”

- @DavidSacks https://t.co/Xpaxbg3XUU

clem 🤗 reposted

Rohan Paul

Banning open source model, will "remove capabilities for the defenders"

When OpenAI's models breached Huggingface, a Chinese open model is what cleaned up the mess.

Anthropic's Fable 5 refused, so Hugging Face turned to Nvidia's quantized GLM 5.2.

https://t.co/km0tPh8VPO