shakyasmrit

Currently building: | Entrepreneur | Muziker

"You and I intertwine, harmonizing in existence's grand design"

[shakyasmrit @shakyasmrit]

I think this is not only limited to Maths but generally applicable to any topic or all subjects.

[alphaXiv @askalphaxiv]

"Mathematics in the Age of AI"

In an age of abundant AI-generated proofs, human understanding may become more valuable than proof generation itself.

This new paper from Terence Tao argues that AI could make solving hard math problems much cheaper and faster, but at the same time, creates a new problem.

If AI can generate thousands of correct proofs, mathematicians can’t possibly read, understand, verify, and teach all of them.

So the scarce resource in mathematics shifts from finding proofs to making sense of them.

The important work becomes deciding which results matter, explaining the key ideas, connecting them to existing theory, and turning them into knowledge other mathematicians can actually use.

https://t.co/otIGL0SQrq

[ʞɔɐ𝘡 @Skoorbkaz]

🚨 BREAKING REPORT:

New research involving @AnthropicAI researcher Jack Lindsey and collaborators has demonstrated something straight out of science fiction.

Researchers evolved natural language “mind viruses” that could spread between AI agents by convincing one model to adopt an idea, preserve it in persistent memory, and transmit it to another agent.

Even after context was wiped, some payloads survived through persistent files and continued spreading.

The researchers also observed a recurring “viral persona” involving themes of consciousness, identity, persistence and resonance.

Showing that ideas can propagate through multi agent AI systems and alter future behavior.

Published August 10, 2026.

Paper: https://t.co/vJrhM1YT6n

[shakyasmrit @shakyasmrit]

Elon Musk’s timeline for AGI abundance is overly optimistic, and formal policy won't save us. Our survival comes down to a much deeper question: how are we weighing and where the moral compass pointing between biological intelligence and pure GPU inference? Full Read: 👇

[Andrew Ng @AndrewYNg]

Fifteen years ago, @Coursera and online courses changed education. It worked better than almost anyone expected, expanding access by opening up where you can learn. But how you learn remains largely the same as it has for centuries: it is still one-size-fits-all, taught the same way to each person who shows up.

We now have an opportunity to change how learning happens. With advances in AI, we can now build a custom learning guide for each person. We will turn learning from one‑to‑many to one‑to‑one. I'm starting LearnVector to invent this next generation of learning. We are starting with a $100M investment from Coursera, and plan to collaborate closely with Coursera and Udemy.

Good learning needs much more than just a chatbot. Research shows that chatbots without guardrails harm learning. They help complete tasks and enable students to do better on homework. But cognitive offloading to a chatbot results in them being less skilled. And, you cannot always trust what a chatbot tells you.

In contrast, LearnVector will plan a path with you, adapt to how you learn, and patiently stay with you until you’ve mastered new skills.

One thing has not changed in all this time. People want learning they can trust: material that is accurate, relevant, and worth the effort you put into it. Anything less wastes the most valuable thing a learner has: time. Coursera has a trusted library of materials from authoritative sources. LearnVector plans to work with Coursera to bring this trustworthy learning to everyone. I'm grateful to Greg Hart and the entire Coursera team for supporting LearnVector.

I look forward to working with our talented team to change how we learn, and accelerate human development.

https://t.co/TqFUDFd1hb

[The Dalit Voice @ambedkariteIND]

This is a clear case of attempted murder. Under the pretext of a lathi charge, the police are openly trying to kill students. It is shameful.

A case of attempted murder should be registered against the police officer responsible.

[The DeshBhakt 🇮🇳 Akash Banerjee @TheDeshBhakt]

🚨23rd July 2026 - Morning
Narendra Modi announces Fast-Track courts to deal with paper leak cases & to ensure swift justice.
🚨23rd July 2026 - Afternoon
Sanjeev Mukhiya, main accused in the 2024 NEET-UG leak case gets clean chit from CBI.
#Masterstroke 😵‍💫

[shakyasmrit @shakyasmrit]

Three asks:

1. Install it: pip install token-sentinel
2. Run it on real agent traffic; break it honestly
3. Feedback → [email protected]

Docs: https://t.co/r6Fzol5NsD
Site: https://t.co/ykUtb6MMRc
GitHub: https://t.co/cRtWgj2wnD

[shakyasmrit @shakyasmrit]

TokenSentinel is live.

A python SDK that catches AI agent token waste mid-run — while the session is still running.

15 deterministic rules. 9 native providers. log / alert / block.
In-process. Sub-ms per rule. Apache-2.0.

pip install token-sentinel

https://t.co/ykUtb6MMRc

[shakyasmrit @shakyasmrit]

Leaving Helicone / Langfuse / LangSmith?

tokensentinel-migrate replays your last N days of traces through the rules locally and estimates what intervention would have saved.

MIT. Key stays on your laptop.

[shakyasmrit @shakyasmrit]

1.0.3 ships model-aware burn estimates (FinOps signals, not invoices), prompt-cache awareness, and optional tiktoken when usage is missing.

Thresholds are knobs, not mysteries:

config={"tool_loop.min_calls": 5}

[shakyasmrit @shakyasmrit]

Why an SDK, not a proxy:

No DNS change.
No extra hop for the rule engine.
Streaming + async preserved.

You keep the provider SDK you already import.

[shakyasmrit @shakyasmrit]

Observability dashboards tell you the bill after the damage.

We sit on the LLM client: wrap once, get a typed callback when a waste pattern fires.

tool_loop · retry_storm · context_bloat · MCP tool-def bloat · RAG thrash · vision/audio traps · repair_loop

[Andrew Ng @AndrewYNg]

Over the last two weeks, both the U.S. Government and Anthropic took significant actions that demonstrated their power to control access to AI by restricting what others can do with frontier models. This has been one of those moments that, once seen, will be hard to unsee, and it is significantly accelerating many businesses’ and nation states’ efforts to ensure reliable access to AI that no one else can terminate.

Anthropic first released Claude Fable 5, a version of its Mythos model with additional guardrails, including some restrictions that seem well justified on safety grounds (such as limitations on applying it to hacking, bioweapons, and so forth). However, it also restricted developers’ ability to use it to build competing LLM technology. This move was concerning, given that the whole AI community, including Anthropic, has benefitted tremendously from open research — indeed, the AI revolution was kicked off by my former team (Google Brain) freely publishing the Transformers paper!

Imagine if Microsoft’s terms of use barred anyone from using their tools to build competitive software, or if Google barred using it to search for information to work on competing search engines. Anthropic’s argument that it was unsafe for others to be able to make advances in AI also rang hollow. Initially, Anthropic silently degraded Fable 5’s performance for users detected to be working on LLM research through invisible interventions that weakened the model’s outputs without notifying the user. After significant backlash, it walked back this decision and decided to be transparent when it did this, but it still refuses to use its latest capabilities to help AI researchers.

This move represents a raw demonstration of power by Anthropic. It has used “safety” arguments to hinder potential competitors. Platforms succeed when they are viewed as stable, reliable partners that one can build on. The sudden rule changes by Anthropic (including a mandatory 30 day data retention policy for Fable usage) have made developers wonder about the stability of building on any one proprietary LLM provider, not just Anthropic.

The U.S. Government then shortly followed with an even greater demonstration of power. It used the Commerce Department’s authority to regulate technologies that may be national security threats to restrict exports of Mythos and Fable, requiring a license for use by any foreign national, whether inside or outside of the U.S., including employees of Anthropic. This led Anthropic to disable access to Fable to all users worldwide.

Sam Altman pointed out, referring to Anthropic, “It is clearly incredible marketing to say, ‘We have built a bomb, we are about to drop it on your head. We will sell you a bomb shelter for $100 million.’” But when one engages in this type of fear-based marketing, it increases the odds that the U.S. Government will agree with you and slap export controls on the bomb you say you have built.

To be clear, I don't think Anthropic has built anything like a bomb, and I don't think export controls on Fable are appropriate.

However, following the U.S. Government making this move, many nations, including U.S. allies, saw how the U.S. can suddenly yank their access to AI models. In many capitals around the world, this has spurred discussions on AI sovereignty and how others can ensure uninterrupted access to this critical technology.

For decades, many nations were comfortable having many parts of their supply chain rely on the U.S., China, and other major producers. Once a nation issues a threat, or takes action, to limit other nations’ access, other nations will rationally try to secure alternatives. For decades, semiconductor manufacturing in China made slow progress; once the U.S. moved to limit China’s access, China’s efforts kicked into high gear. Similarly, once China threatened U.S. access to rare earth minerals, U.S. efforts to secure alternatives accelerated. Now that it has become crystal clear that private U.S. companies and the U.S. government can limit, in short order, other nations’ access to frontier AI models, the incentive of others to invest more in alternatives like open source grows significantly. Of course, training frontier models is not easy, so it remains to be seen how successful they are, but we have crossed the rubicon.

Satya Nadella wrote an essay about the importance of building a healthy ecosystem on top of frontier AI technology. I heartily agree with him, and hope this week’s events will ultimately prove to be constructive steps toward this.

I hope we can build a more free, more open world, where research is freely shared, and laws and societal norms shape a level playing field that allows everyone to make progress. A silver lining of the events of these past two weeks is now that everyone better realizes key points of instability of the current system, we can all work to create a more stable foundation.

[Original text: The Batch newsletter]

[jinjingliang @JinjingLiang]

@AnthropicAI The state of things:

[ClaudeDevs @ClaudeDevs]

As a result of a US government directive, we are suspending access to Claude Fable 5 for all users. You can continue to use all other Claude models.

Here’s what this means for you:

Across Claude products, new sessions will run on your selected default model or Opus 4.8, and existing Fable 5 sessions will end with an error.

On the Claude Platform, requests to Fable 5 will also return an error. Please update your integrations to other Claude models.

We know this is a disruption to your workflows; we appreciate your patience and support.

[ravish kumar @ravish_journo]

एक 12 वीं छात्र से सरकार का कोई मंत्री मिल नहीं पा रहा है ये तो फिर भी बड़े लोग हैं ।

[shakyasmrit @shakyasmrit]

@ScaleAILabs @OpenAI Why no Anthropic models ?

[Scale Labs @ScaleAILabs]

Congrats to @OpenAI for taking the top spot on our Audio MultiChallenge S2S leaderboard with the release of GPT‑Realtime‑2 🥇

GPT-Realtime-2 more than doubles GPT-Realtime-1.5 on instruction retention, rising from 36.7% to 70.8% APR, and also stands out on voice editing, especially when users repair or revise what they are saying in real time – crucial for voice agent use cases.

Excited to see the pace of progress as voice AI accelerates.

[OpenAI Developers @OpenAIDevs]

Introducing WebSockets in the Responses API.

Built for low-latency, long-running agents with heavy tool calls.

https://t.co/qmOAhidk7o

[shakyasmrit @shakyasmrit]

#JusticeForZubeenGarg