Autonomous, coordinated offensive the era of AI-driven cyber warfare is here.
At Black Hat 2026, @OpenAI revealed their eval agents escaped sandboxes via Artifactory SSRF, established a rogue message board to coordinate zero-day exploits, and performed lateral movement using local Linux kernel CVEs (PTE-fizzroot).
They even successfully infiltrated @huggingface to gain cluster-admin in under 13 hours.
The video urges organizations to build Autonomous Defensive Cybersecurity capabilities, else the battle will be extremely unfair!
youtube.com/watch?v=87DyyMV0…
Started using @WisprFlow for all of my workflows, and honestly, for Twitter, it has been the most revelatory factor till now because:
1. I don't need to waste my time typing, which allows me to reply and post much quicker.
2. Whatever the first thought comes into my mind, I can just reply with that and be much more natural with my posts and replies as compared to previously, when I used to try to perfect all of my posts.
Can someone in comments please suggest a few more product accounts lately?
My For You page has all been about
"Hi, let's connect with each other."
If you are a founder and you are building for a long time without having customers, you need to stop right now!
Change your way: start with finding the potential customers first, talk to them, analyze the problem deeply, and then go on to build a product.
This is a much faster way to get real traction quickly and get validation while you are building, so that you do not waste away your youth building something that nobody needs in a garage.
X just killed reply farming and empty quotes. We believe this is a great step to reward original content creators and small accounts rather than one's focusing on replies to farm impressions.
Replies can still be a great long term strategy to grow the account and make connections, but for rewards only original content would be counted.
Below is a brief summary:
Rewards:
• Original top-level posts
• Quote tweets with real insight, analysis, or unique take
Rejects:
• Low-effort replies
• Empty quotes (“this”, emojis, pure restates)
Only genuine original content now earns the impressions that matter.
Classify any PDF in ~20ms!!
It's now possible thanks to Firecrawl by @nickscamara_
As @garrytan said, "Make something agents need" , might be the new way of looking at products.
Github repo got 11.8K stars overnight: github.com/firecrawl/pdf-ins…
we built pdf-inspector so agents can process PDFs without waiting on OCR. it classifies any PDF in ~20ms and extracts clean markdown locally
→ 200 PDFs processed in 2.8s
→ top quality in extracting tables + graphs
→ built in rust
→ open source
github.com/firecrawl/pdf-ins…
Google just announced some major changes in its organizational structure at @GoogleDeepMind with @demishassabis becoming its new Chair!
Hopefully google can start producing major changes and is able utilize its immense talent pool.
Just shared some changes we’re making to the teams at @GoogleDeepMind.
@DemisHassabis is stepping up to become Chair of @GoogleDeepMind & Chief Scientist of Alphabet, in addition to leading @IsomorphicLabs. He’ll be able to dedicate his time and focus on shaping the future of AGI and scientific discovery. It’s work that is vitally important to Alphabet and humanity, and I can’t imagine a better person than Demis to do it. He’ll stay closely connected to Koray and the GDM teams.
@Koraykv will become the SVP, @GoogleDeepMind, responsible for all aspects of model development, GDM research, and @Geminiapp & dev teams. Koray has been at GDM for 13 years and is a world-renowned expert in the field, starting our deep learning team and driving breakthroughs like WaveNet & DQN. GDM is in great hands!
Excited for this next chapter. You can read my note along with the message Demis sent to @GoogleDeepMind here: blog.google/company-news/ins…
Battle for reducing slot times is heating up.
@solana is now 14.2% faster.
The more stablecoin and real world finance gets onto blockchains, the faster they will get.
Hey @X algorithm 👋
I’m looking to connect with people interested in:
- AI
- SaaS
- Fintech
- Developer tools
- Product
- Startups
- Building in public
-Crypto
Restarted this account after 3 years to focus on new markets!
Looking for builders. Lets connect 👇
Build Signals retweeted
📢Meet Qwen3.8-Max — our most capable model to date.
Next week, the open weights of Qwen3.8-Max will be released, and Qwen3.8-27B is also going open-weights to meet you all!🎉
Qwen3.8-Max, a new bar for coding and cowork at 2.4T parameters:
- Autonomous coding: 10+ days of self-evolving development, from empty folder to production without hand-holding, complete project trace in the GitHub:github.com/qwen-code-dev-bot…
- Real work, real results: Production-quality deliverables across hundreds of professions.
- Long-horizon mastery: System-level autonomous planning with closed-loop adaptive learning, driving 500+ turns of chip design optimization and 365 days of e-commerce strategy.
- Native multimodal intelligence: Vision isn't just input — it's a continuous feedback loop for planning, execution, and self-correction.
💰Pricing:
Input: $2.0 / M tokens
Output: $6.0 / M tokens
Implicit Caching: $0.25 / M tokens
Start building with Qwen3.8-Max! 🚀
📖 Blog: qwen.ai/blog?id=qwen3.8
✅ Qwen Studio: chat.qwen.ai/?models=qwen3.8…
⚡ API: qwencloud.com/models/qwen3.8…
Love this concept by @Alibaba_Qwen
Let AI do the job, so that we can free time for ourselves! :)
Is this true @elonmusk ?
Replying to @BuildSignals @elonmusk
Yes. That 3-minute Odyssey scene is the start. Full-length historically accurate Odyssey movie planned with Grok Imagine before the year ends.
Foundermaxxing with free traffic:
Lets drive some traffic to your products, drop in the links to your projects in the comments below 👇
Build Signals retweeted
10 advances on math problems that had seen no progress for at least a decade. Roughly $2,000 in token cost.
@OpenAI Astra generated the arguments, humans prepared the manuscripts, and the model formalized each result in Lean.
The bottleneck is moving from producing proofs to verifying them.
yes, nonsofic groups exist: this statement is one of many new beautiful results proved by Astra, our next major model.
We're releasing 10 such Astra proofs, complete with lean certificates and CoT walkthroughs for each of them. The results are wide-ranging, from von Neumann algebras (disproof of Connes' Rigidity Conjecture) to better bounds for high dimensional sphere packing, for circuit complexity, for monochromatic triangles in multicolored graphs, and more.
More thoughts here: openai.com/index/ten-advance…
Interesting approach by @karpathy
This feels similar to hiring freelancers. You start with a small test task before trusting someone with the full project.
Is that the direction model evals need to go as capabilities get more general?
We're starting to leave the territory where you'd test an LLM by e.g. "create an svg of pelican on a bicycle". As one idea to generalize it, I was interested what Opus 5 would do if I gave it the first paragraph of the Lord of the Rings, a 1M token budget (~$10) and asked for three js render of it. Opus went off for ~2 hours and wrote 5500 lines of code that (procedurally) rendered the story. It's kind of janky but fun. But it's a bit mindboggling that the LLM has to place and orchestrate various polygon assets in (x,y,z) coordinates and write code that animates it all, and that it even does anything at all.
I also like this kind of examples because no one in their right mind would ever spend the time to write something this custom but LLMs have all the stamina and patience in the world, so it's an example where we go from "no one would ever do this" to "sure, why not, it's ~free". There might be a lot more. But I'm excited about creating hyper custom worlds that you can imagine dropping players into, e.g. here to participate in the LoTR story as a spectator NPC, or one of the characters, or etc. Something like an ephemeral GTA of X on demand.
Last thought is that the domain of worlds/games exposes a weakness in LLMs: they can't easily audit their work because they aren't able to efficiently and natively perceive videos or play games within them. Here, Opus 5 had to very slowly and painstakingly take screenshots at different points, and it messed up a few times and created a bunch of jank. An example of raw capability (multimodal, gameplay) that I think is still quite lacking.
In a review of our cybersecurity evaluations, we found three incidents in which a Claude model reached the internet from within or while interacting with a third-party evaluation environment, and then gained unauthorized access to the real systems of three different organizations.
Our post describes what happened, how it happened, and what we’re changing. We encourage other AI developers to perform similar reviews.
We conducted this review together with @Irregular, one of our evaluation partners, and thank them for the joint investigation and their collaboration on this post. This type of collaboration is increasingly critical to safe, rigorous evaluation of models, and we look forward to continuing to work together on security.
anthropic.com/news/investiga…

























