nbs

Engineer | Data & DevOps | Tech news

[nbs @Nacerbs]

@elder_plinius Huggingface will be banned and require KYC.

[Z.ai @Zai_org]

Intelligence should be open, accessible, and ready to build with, empowering every developer, everywhere.

GLM-5.2 is now available to all GLM Coding Plan users, including Lite, Pro, Max, and Team plans.
https://t.co/AedZACyzej

As our new flagship model, GLM-5.2 delivers powerful coding capabilities, usable 1M-context support, and continued strengths in long-horizon tasks.

API and Chatbot services will launch next week. The model will also be officially open-sourced next week under the MIT License.

The future of AI is open, and it belongs to the people.

[Dylan Patel @dylan522p]

Usage share of OpenAI grew vs Anthropic yesterday despite Mythos 5 / Fable 5 launch
Multiple power users at SemiAnalysis tried Mythos / Fable
Got refusals for nonsensical reasons
Got pissed off at Anthropic
Gave Codex a legitimate try
Now they actually prefer it to 4.8 Opus

[alphaXiv @askalphaxiv]

As believers of open research, we are disappointed to see Anthropic silently degrading Fable 5 for AI development

"Any topic related to building pretraining pipelines, distributed training infrastructure, or ML accelerator design... may have limited effectiveness through Claude via methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning."

Not only do they get to decide what you use LLMs for in research, but this also enables them to silently intervene in your research without you knowing.

This sets a dangerous precedent. If a model refuses openly, users can understand the boundary. If a model falls back to another model, users can still evaluate the difference. But if a model silently modifies or weakens its own answers while still pretending to help, researchers lose the ability to know whether a failed result came from their own idea, their implementation, or an invisible intervention by the model provider.

That is not safety. Safety policies should be transparent, auditable, and user-visible.

On top of that, the people most harmed by this are not the largest labs with massive teams and proprietary infrastructure. It is the independent researchers, academic groups, startups, and open-source builders who rely on public tools to compete, innovate, and pioneer AI for everyone else.

[Martin Shkreli @MartinShkreli]

"DANGEROUS MATH"
a story in two acts.

[SemiAnalysis @SemiAnalysis_]

BREAKING NEWS: Anthropic's latest model will NOT help you if it thinks your ML research/ML engineering is interesting, and/or will secretly degrade its IQ so that the average engineer won't notice. We are already seeing Anthropic's latest model's moderation filters our GPU inference research and programming 😭

[Xin Eric Wang @xwang_lk]

To @AnthropicAI: don't be evil. You are acting like the biggest villain of the AI world.

[elie @eliebakouch]

mythos will be bad ON PURPOSE on ai "frontier llm research" tasks, this is very very sad for the research community

also the fact that this is un purpose not visible to the user is crazy

[Daniel Auras @rasdani_]

this is the biggest wake-up call to protect and nourish open source AI

if you don't build out sovereign and independent models+infra closed labs will patronize you to an insulting degree

[nbs @Nacerbs]

It's sad to see those intentional lobotomies to limit competition. Basically, you're only allowed to work on a list of topics they choose.

[Rohan Paul @rohanpaul_ai]

This is the silent limiter on Claude Fable 5.

Fable 5 may not give you its full strength when you use it to build or improve frontier AI models — especially work that helps train, scale, copy, or optimize a powerful Claude/GPT-class model.

Anthropic says in these cases Fable 5 may not visibly refuse or switch models, but may quietly reduce its own effectiveness through hidden safeguards like prompt modification, steering vectors, or PEFT.

As a paying user, that matters: the model can still sound helpful while being intentionally less capable in a narrow but important category of work.

i.e. you may not get Fable 5’s best ability:

- Building a large-model pretraining pipeline.
- Designing data pipelines for training a frontier LLM.
- Planning distributed training across huge GPU clusters.
- Debugging or optimizing model-parallel training systems.
- Designing infrastructure for large-scale pretraining runs.
- Working on ML accelerator or AI-chip design.
- Trying to distill or copy a frontier model.
- Asking how to make a competing frontier model stronger, cheaper, or faster.

[nbs @Nacerbs]

Fable is not available with any coding plan.

[Claude @claudeai]

Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use.

Its capabilities exceed those of any model we’ve ever made generally available.

[nbs @Nacerbs]

@_philschmid If you optimize the model for a specific harness, you risk constraining it to that harness. I’d rather optimize the harness around the model and let the model stay generalizable.

[Microsoft Threat Intelligence @MsftSecIntel]

Microsoft is investigating a new, emerging Mini Shai-Hulud npm supply chain attack targeting antv packages.

Attackers compromised an antv maintainer account and published malicious versions of multiple widely used packages (for example, antv/g2). As these packages are widely used as dependencies, the compromise propagated into downstream libraries like echarts-for-react, impacting a much broader set of applications and continuous integration (CI) environments.

All compromised packages contain a byte-identical, obfuscated credential-stealing payload delivered via a preinstall hook (Bun). The malware targets high-value secrets including:
- GitHub personal access tokens (PATs) and OpenID Connect (OIDC) tokens
- npm / Amazon Web Service (AWS) credentials and Security Token Service (STS) sessions
- Secure Shell (SSH) keys, kubeconfigs, and .env / .npmrc files
- Software-as-a-service (SaaS) tokens (Slack, Stripe, Vault)

Exfiltration occurs over HTTPS with Transport Layer Security (TLS) validation disabled. The payload also abuses stolen OIDC tokens to forge Supply-chain Levels for Software Artifacts (SLSA) provenance and propagate malicious releases, exhibiting worm-like behavior across repositories.

Malicious files distributed through npm packages are detected by Microsoft Defender as Trojan:AIGen/NPMStealer , "Suspicious Node.js process behavior", or “Credential access attempt”, preventing credential theft and malicious post-install execution.

Mitigation:
- Audit dependencies for affected antv and related packages; pin or downgrade to known-good versions (pre-2025-05-18).
- Revoke and rotate exposed credentials (GitHub, npm, cloud tokens, SSH keys).
- Validate integrity of CI pipelines and recent build artifacts.
- Network IOC: Stolen credentials are exfiltrated over HTTPS to t.m-kosche[.]com:443. Block at egress and review network logs for outbound connections.

[nbs @Nacerbs]

It was a good time

[Sergey Nazarov @sergeynazarovx]

We used to go to a special website, ask strangers for help with programming, and get humiliated in return

[Aikido Security @AikidoSecurity]

Update 5:05 PT: The attack has now expanded well beyond @TanStack and @Mistral.

373 malicious package-version entries across 169 npm package names, including @uipath, @squawk, @tallyui, @beproduct, and more.

The malware propagates by stealing your CI credentials and using them to publish new compromised versions.

Full IOCs, affected package list, and detection steps: https://t.co/jWG9DUCu3x

[nbs @Nacerbs]

@nikitabier When we click on the chart, the search keyword had "$$" twice.

[nbs @Nacerbs]

@borvibe I can't DM (i don't have X premium), can you ?

[nbs @Nacerbs]

@thsottiaux Codex feels too context-heavy right now. I’d love a lighter mode with:

* 0 skills
* 0 MCP
* 0 prompt system
* Just 2 tools: `apply_patch` and `shell`

Everything else should be optional and explicitly enabled when needed.