SteveB retweeted
We're giving away a Hogwarts Legacy custom wrapped NVIDIA GeForce RTX 5090 to celebrate its official release with DLSS 5 🪄
To enter:
🟢 Share this post
🟢 Comment #RTXON
Terms and Conditions: nvidia.com/en-us/geforce/con…
Introducing Jev @typesafeai powered social-api
Try it at treg.to/social
- One API to access any social data
- Track every mention of you & your competitors
- Find trending posts in your niche, filtered by Jev
- Under $0.05 to pull 1,000 competitor ads
Open source, 0% markup
👇 Repo link below
SteveB retweeted
Today we release Mirage: A 22 MB visual-language model that runs scene descriptions + object detection + OCR + segmentation + spatial relations analysis + extractions + decisions, in a single pass.
It can do all that in 74 ms on Samsung Galaxy S26 NPU or 107 ms on its CPU.
Mirage has a 7.8M encoder + a 40.8M decoder at 2bits, and describes images in English, German, French, Spanish, Italian, Dutch and Polish.
We trade general language capacity, to compete top small VLMs today (SmolVLM2-500M, LFM2.5-450M and Florence2-230m) on these tasks.
On 256 VQAv2 questions, feeding Mirage's structured output and full trace to text-only Qwen3-0.6B raised its score from 9.3 to 31.3 out of 100, without fine-tuning either model.
Read more and benchmark it yourself here:
cactuscompute.com/blog/mirag…
SteveB retweeted
an absolutely beautiful and informative blog post! one of the biggest anti-patterns we see with jev is just plugging it in to make Big Decisions instead of having code do what it's best at and jev for just the parts that require judgment 🤌
THIS is how we transform software!
SteveB retweeted
Voice direction & distance-aware UI.
The demo shows Voice Ring + Libraries Voice Position model, where the UI reacts to voice direction and distance. The ring also changes its color based on speech emotion. Ready to use with SwiftUI on Libraries.dev
SteveB retweeted
we made an open-source Grok Bot with unlimited usage!
meet @mausbot_
use your existing subscriptions: Claude, Codex, or even local models.
Try it here - mausbot.com
SteveB retweeted
LibreYOLO 1.7.0 is out, and this one is special: image to 3D!
The first model is Speridlabs Idol by @speridlabs, and the quality is stunning. One photo in, a 3D Gaussian splat out, in three lines.
Apache-2.0, weights straight from their Hugging Face.
libreyolo.com/docs/models/sp…
iOS app is live!!!
apps.apple.com/app/id6827958…
This quoted post is unavailable.
SteveB retweeted
Great to see Ming-3.0-tts-0.5B running locally on an RTX 3090! In @ItsmeAjayKV’s test, a 5-second sample of his own voice was enough for cloning—even with fan noise in the recording. 🫶 Thanks for sharing, AJ! We’d love to see what you build next.
Tested voice cloning with Ming-3.0-tts-0.5B by @AntLingAGI and it is even more insane.
For a model of this size, voice cloning happens really well, i tested my own voice, half drunk, in a room full of noise (fan noise mostly) and it instantly cloned it.
It needed just a 5-second sample of my voice, and it speaks faster than real time: about 4 seconds of speech in 2–3 seconds.
All running locally on my RTX 3090. Ming takes about 3.3 GB of VRAM, and the whole model is under 3 GB on disk.
Great time for Local AI.
SteveB retweeted
Your Harness. You Define It.
Meet Creator Mode in DeepSeek Harness.
Turn ideas into plugins that you can use, from a design workspace to a sandbox game or a 3D LLM visualizer.
What will you create?
Sound cool..
I will be the first person claim the "System Sub-zero"
a lot of decision models came out in the last two months. almost all of them work the same way. they read text, wait until the whole input has arrived, and then give you an answer
that works for a support ticket. it doesn’t work for a robot, a phone call, or a video feed, where the input never really ends and the decision has to happen while it is still coming in
so we spent half of our YC money training a model:) RightNow takes text, PDFs, images, voice, code, robot state and video, all in one model, and you can stream up to 1M tokens of context into it. it updates its decision as each piece arrives. on text it decides in 30 ms and we will make it less with our kernel optimization
we trained it with what we call Reflex Training. the current decision models read everything first and answer once. RightNow is trained to decide on whatever has arrived so far, to hold back until the evidence is there, and then commit. it serves on what we call Reflex Architecture which keeps a probability for every option and updates it as each part of the input comes in
we call this kind of model “System Zero”. system 1 is fast thinking and system 2 is slow reasoning. system zero is the step that comes before both, which is just deciding
we will publish a technical paper on Reflex Training and Reflex Architecture. the model itself will stay closed source and available via RightNow API
this is our first checkpoint and it’s still a little buggy. we launched it early because the fastest way to make it good is to have people use it:)
SteveB retweeted
Introducing Granted!
I bookmark a lot on X and almost never go back to it. So I built something that does.
→ Every night, agents read my X bookmarks
→ Research ideas, pick the best one
→ And build a working prototype.
Every morning I wake up to a startup brief + a live app on my phone.
Open Source, sharing soon!
12 years. One company. A 9–5 routine.
I’m stepping away to build products at Orchexa.
Our vision: an Agent OS where AI goes beyond chat—using real tools, running workflows, and working alongside humans to deliver outcomes.
Less hype. More shipping. #BuildInPublic
SteveB retweeted
🎉 NVIDIA Nemotron 3.5 Transcribe is here—with day-0 serving through vLLM + NeMo Speech.
40 languages. Recordings up to an hour. Promptable transcripts, speaker labels and audio Q&A.
Open weights in BF16, FP8 and NVFP4.
Meet NVIDIA Nemotron 3.5 Transcribe 🎙️
An open-weight, promptable 30B MoE model with ~4B active parameters that brings transcription in 40 languages, speaker attribution, translation, contextual prompting and audio understanding into one checkpoint.
Watch it keep track of who said what when everyone’s talking at once.
1/ 🧵
SteveB retweeted
So one of our ambassadors @divagr1925 has been working on something cool
He found a way to use Qwen's Gated DeltaNet state as memory, and built a 32-bit RISC-V CPU directly into the model's weights. So instead of relying on predicting the answer to a calculation, the model can execute instructions internally. It can also run C and MicroPython programs.
He calls it Qwenputer, love the name btw. The results so far are pretty impressive. On one arithmetic benchmark, accuracy jumped from 48.6% to 100%.
Pretty cool to see developers experimenting with Qwen's architecture. Great work, my friend!
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Introducing Reality-Aware Rendering in @Simulon, a completely new way to create with the real world.
Place neural assets with your phone and act out the scene. When you stop recording, Simulon renders the take, reading everything in it (what you do, what you say and the place around you), and your assets respond to all of it.
The final is regenerated from your recording: a new performance of the scene, not a copy of the footage.
Available now on iPhone. Coming to Android soon.


























