building soverign intelligence in @premai_io
Joined July 2017
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c retweeted
Introducing TimesFM-3, a state-of-the-art time series foundation model that enables accurate multivariate time series forecasting in a single forward pass, significantly outperforming other forecasting models across major benchmarks.
More on the blog →goo.gle/4x5WGpD
ALT TimesFM-3 architecture.
c retweeted
Excited to announce the launch of Cyberscan - Prem's proprietary security agent for vulnerability detection built in partnership with @ArkLabsHQ and the @Breez_Tech
Powered exclusively by open-source models like Kimi-K3, Qwen-3.8-Max and more, Cyberscan has helped over 20 teams find mission critical vulnerabilities in their codebases, preventing massive liabilities.
Starting Today, Cyberscan is available for public access (link below) with $25 in free-credits for new users. Login with your github, connect a repo and it takes care of the rest - surfacing vulnerabilities that you definitely might have missed out.
c retweeted
Stanford is definitely cooking something crazy.
By enabling self-verification during the intermediate process, Deepseek-V4-Flash easily outperforms Fable.
11x cheaper and a much higher Terminal bench score.
This is exactly why I love X. People just casually drop massive breakthroughs in a single post.
Github ⬇️
Scaling self-verification with DeepSeek V4 Flash beats Claude Fable 5 on Terminal-Bench 2.1, while being 11x cheaper 💰
As open-source models become more capable, they can now generate large numbers of high-quality candidate solutions and verify their own outputs at very low cost.
For example, we find that sampling just 5 solutions with DeepSeek V4 Flash and ranking them using the same model with LLM-as-a-Verifier can lead to a significant boost in accuracy (79% → 88%), outperforming closed frontier models on Terminal-Bench.
Try it out today: github.com/llm-as-a-verifier…
More on verification scaling in my previous post.
c retweeted
call me crazy but the first AI agent most companies should build is an autonomous analyst.
you can build one using Kimi K3.
it watches your competitors while you sleep, remembers every move, and wakes your team with the launches, pricing changes, and positioning shifts they need to act on.
don't bookmark this if it crosses your timeline.
paste the full article into Kimi and tell it to build the first version for your market.
c retweeted
🔥 A Qwen3.8-27B user is getting fast on a SINGLE 24GB RTX 4090.
Huge credit to Reddit user u/gavwhittaker, who spent time dialing in a reproducible llama.cpp configuration and shared the entire setup with the LocalLLaMA community.
Their system:
🎮 RTX 4090 — 24GB
🧠 Ryzen 7800X3D
💾 128GB system RAM
🤖 Qwen3.8-27B UD-Q4_K_XL
📚 92K context
⚡ Flash Attention
💾 Q8 KV cache
🚀 MTP speculative decoding
✅ No model spilling into system RAM
And they're reporting generation speeds ranging from:
⚡ ~44 → 134 tok/s
on a single RTX 4090.
The interesting part isn't just the peak 134 tok/s.
Look at what's happening on one consumer GPU:
**27B dense model
+ 92K context
multimodal projector
speculative decoding
+ 24GB VRAM**
Their MTP configuration is particularly aggressive:
🧩 --spec-type draft-mtp
🔮 --spec-draft-n-max 6
🎯 --spec-draft-p-min 0.82
And they shared the entire llama.cpp command line, so other 4090 owners can actually reproduce and improve it.
This is why community benchmarking matters.
Localmaxxers are just figuring out how to squeeze a LOT more out of the hardware we already own.
👏 Credit again to u/gavwhittaker for doing the tuning and sharing the config.
c retweeted
BREAKING！
Apple Intelligence has finally completed its regulatory filing in China.
This means it's now one major step closer to officially launching for users in China.
I'm already looking forward to the iPhone 18 Pro.
Also, I noticed that Samsung Galaxy AI has completed its regulatory filing in China as well.
c retweeted
Today we're launching OpenUI Cloud
We've spent months arguing AI deserves more than text.
The uncomfortable truth is Generative UI in production needs much more than just rendering.
The boring parts - validation, error correction, fallbacks, versioning, audit trails - eat up 80% of the time and become the critical factor in deciding whether your Generative UI agent reaches production or dies trying.
OpenUI (open source) handles the rendering.
OpenUI Cloud handles that 80% nobody should have to rebuild.
> npx @openuidev/cli@latest create
insane team, insane product. what an honour
Today, we're excited to announce the launch of our Proactive AI Workspace - Fluso!
Built in partnership with global law firms, hedge funds, and hospitals, Fluso changes the way teams work with AI.
50+ customer interviews taught us one thing - organisations that have invested heavily in AI assistants for knowledge work face 3 major challenges:
1. Low utilisation
2. Lack of standardisation
3. High costs
Fluso solves that.
It plugs into your organisation's tools, builds a deep context graph about each user and automatically starts detecting tasks that a team member needs to complete. Teams are no longer left wondering what their assistant needs to work on, they just approve the tasks Fluso detects and let it flow through them.
Built on 3 core foundations, our initial users have have an overwhelmingly positive feedback on the impact of each:
1. Private: Fluso is powered exclusively by open-source models, with an option to access them confidentially.
2. Proactive: Users loved when Fluso reminded them of tasks it offered to complete that were lost in slack threads and meetings
3. Price-sensitive: Fluso offers 5x more tokens for the same plan as compared to similar AI workspaces, making it extremely cost efficient.
Stop thinking and start flowing now 👇
c retweeted
The AI industry has a dirty secret nobody talks about.
Your data is visible to every LLM provider you use today.
Every piece of sensitive data, proprietary strategy, and private thought you feed into these systems is readable, storable, and exploitable.
This thought made us very uncomfortable.
For AI systems to be truly useful, you should be able to expose sensitive information to them with absolute confidence. 18 months ago, we partnered with SUPSI in Lugano to answer this:
Can you get on-premise security guarantees while using cloud LLMs?
We're releasing our first research paper, Privacy-Preserving LLM Inference in Practice: A Comparative Survey of Techniques, Trade-Offs, and Deployability, covering what we learnt about the state of privacy in AI today.
Link in the replies 👇
c retweeted
Prem Studio also ships with all the APIs you’ll need to build your model training pipelines!
You can now programmatically upload your datasets, launch and monitor fine-tuning jobs, run comprehensive evaluations, and deploy production-ready models, all through simple REST API calls. This API-driven approach is designed for automation, enabling you to seamlessly integrate advanced AI management into your applications, CI/CD pipelines, and backend systems.
To make the transition effortless, our inference API is fully compatible with the OpenAI client library.
This means that once you train a model with Studio, switching to Prem's inference is just a line of change!
Today, we’re excited to announce that Prem Studio is available for public access!
Built in collaboration with design partners from Fortune 50 companies, US healthcare providers, and compliance firms in the EU, Studio is an end-to-end platform for building specialized LLMs.
Studio makes it possible for you to build your own custom language model by fine-tuning 30+ small language models without writing any code. The platform handles all the heavy lifting from dataset management, selecting the best base models, managing training infrastructure, running evaluations, and deploying inference endpoints.
Teams using Studio, on average, achieve 10-30x model compression while maintaining 98% accuracy on most tasks. Some even outperform frontier LLMs on domain-specific tasks.
Prem Studio models are fully self-hostable, meeting the strict data sovereignty and security requirements of our enterprise and healthcare partners.
If you’ve got a dataset, you can ship a custom model now. Sign up below and claim free training credits!
c retweeted
Today, we’re excited to announce that Prem Studio is available for public access!
Built in collaboration with design partners from Fortune 50 companies, US healthcare providers, and compliance firms in the EU, Studio is an end-to-end platform for building specialized LLMs.
Studio makes it possible for you to build your own custom language model by fine-tuning 30+ small language models without writing any code. The platform handles all the heavy lifting from dataset management, selecting the best base models, managing training infrastructure, running evaluations, and deploying inference endpoints.
Teams using Studio, on average, achieve 10-30x model compression while maintaining 98% accuracy on most tasks. Some even outperform frontier LLMs on domain-specific tasks.
Prem Studio models are fully self-hostable, meeting the strict data sovereignty and security requirements of our enterprise and healthcare partners.
If you’ve got a dataset, you can ship a custom model now. Sign up below and claim free training credits!
c retweeted
She can put her point across just as well as you can. We are committed to addressing unconscious gender bias that lies hidden in everyday work life. We want to unmask it, and deal with it. Know more: infy.com/3TuU7wR #SpotItToStopIt #InspireInclusion
