rachit

In love with AI & what’s next

[rachit @rachiitgr]

@vivistac lo probaré hoy mismo!

[rachit @rachiitgr]

@hytmIA El anuncio crece cuanto más lees. No es otro modelo. Es la capa que se queda corta cuando el modelo crece.

[rachit @rachiitgr]

everyone keeps scaling compute. the actual wall is memory.

volantis uses light to move data 10x farther than electrical wires. if this works, coding agents finish in seconds instead of hours

[Tapa Ghosh @semiDL]

Excited to announce Volantis's $88M Series A.

We are solving Al's memory bottleneck by using optics, enabling chips with huge amounts of fast & cheap memory.

By boosting both the memory bandwidth and capacity per chip by orders of magnitude, we enable ultra-fast inference (up to 10,000 tps/user) for large models (>10T) - with low $/tok to boot.

Initially, this will enable insanely fast agents - think coding agents that finish in minutes or even seconds instead of hours.

More excitingly, optics is a fundamentally scalable way to increase memory systems. Not 2X/year, but by orders of magnitude across new generations. This will enable a structurally new Al industry, including restarting scaling laws, holding entire repos in context windows & more.

Our team has pioneered many core semiconductor technologies: the 1st CoWoS product, early HBM, the 1st silicon photonics CPO systems, the 1st high volume tunable VCSELs, the 1st processors to directly communicate using light & more.

We’ve already sent data >10× farther than equally tiny electrical wires inside a chip package. Our next iteration is already taped out and targets world-record bandwidth density over relevant distances, read more: https://t.co/ljYTimdcbJ

[rachit @rachiitgr]

Tavus me dio acceso anticipado a griffin lite y ahora entiendo por qué no sueltan el grande

→ no lo lanzan: dicen que es demasiado convincente para soltarlo ya
→ nvidia lo pone #1 en su benchmark de video full-duplex, a 0.09 de un humano real
→ y es el primer modelo en pasar el test de turing
→ lo probé cara a cara y se nota

[Tavus @tavus]

Introducing Griffin, the first model to pass the video Turing test.

48% of people who talked to it live thought it was a real human. Previous systems have had a pass rate <3%. It is #1 on NVIDIA's benchmark for full-duplex AI video.

It’s the first Human Interaction Model (HIM).

[Tavus @tavus]

Introducing Griffin, the first model to pass the video Turing test.

48% of people who talked to it live thought it was a real human. Previous systems have had a pass rate <3%. It is #1 on NVIDIA's benchmark for full-duplex AI video.

It’s the first Human Interaction Model (HIM).

[rachit @rachiitgr]

@brenzhills next trip: los suburbios de barcelona 😭😭

[rachit @rachiitgr]

@yuliaisc estaría bien comparar los dos usando exactamente el mismo contexto y el mismo prompt

[rachit @rachiitgr]

@saidstetic time to make money again G🙏

[rachit @rachiitgr]

@dravenip sub second decisions at that price is kinda crazy

[alex @alextalksai]

Anthropic just released a 37-minute guide on how to build Al agents that can automate an entire business.

It's free, and it comes straight from the engineers who built Claude.

Agents that actually work, delegate tasks, and get things done on their own.

Save this post 🔖

[rachit @rachiitgr]

@deanwperkins lo que no se automatiza es entender por qué la gente compra, y eso se aprende hablando con clientes

[rachit @rachiitgr]

@alextalksai bastante útil la verdad me lo guardo para acabarlo esta noche

[rachit @rachiitgr]

@MikuBTC yo tampoco

[rachit @rachiitgr]

@romandevz Muy interesante la relación entre contenido, backlinks y visibilidad en buscadores de IA.

[rachit @rachiitgr]

tú dentro de 4 años yendo al trabajo a las 6am porque seguiste scrolleando y no viste el artículo más importante de SEO del año

[Dean W. Perkins @deanwperkins]

https://t.co/iFbImRtSBm

[rachit @rachiitgr]

@deanwperkins chat gpt se come al mundo rn

[rachit @rachiitgr]

@arceyul for realll😭

[Nico @nicos_ai]

Sigan a este tipo si quieren aprender cosas realmente útiles relacionadas con la IA

no falla una

[Higgsfield AI 🧩 @higgsfield]

Introducing OpenAI’s Dots x Higgsfield.

Your always-on Higgsfield creative crew keeps working while you’re away.

Check in by text, call or email, and pause the work whenever you need.

Powered by GPT-6.1 Sol.

[Mehul @mehul]

After 9 years. 16K+ family homes. 500M sqft inside real homes covered, we know home robots are being built in wrong order.

So we built Matic the way nature grows a child.

Finally, sharing our vision:
1.⁠ ⁠Why robots get stuck at the demo
2.⁠ ⁠Why labs can't ship robots
3.⁠ ⁠Why we started with eyes, not hands
4.⁠ ⁠The 99.999% rule in robotics
5.⁠ ⁠Where Matic is going next

1. Why most robots get stuck at demos

Robot demos look brilliant in a room arranged around its limitations: familiar lighting, predictable furniture, nothing troublesome on the floor.

A family’s home makes no such accommodations. There are cables, toys, shifting rugs and, occasionally, dog poop. Yes, humanoids will need to avoid that too.

Repeating a task under familiar conditions of uncluttered floors is not the same as handling an unfamiliar home with all its chaos.

2. Why labs can't ship robots

SLAM (Simultaneous Localization and Mapping) is how a robot maps its surroundings and locates itself within them. Ask most academics and they'll tell you it's a solved problem.

But real homes are the most chaotic spaces that exist.

There are glass doors that look like open doorways, mirrors, stairs, rugs, charging cables, and Legos placed all around.

So ask yourself: if indoor mapping and navigation is "solved," where are the robots? Why aren't airports, hotels and grocery stores full of them?

Calling it “solved” misses the question families actually care about: can I leave this thing alone and trust it?

3. Why we started with eyes, not hands

Nature doesn't give birth to a fully working human. We took our cue from how nature develops humans: capabilities built on one another.
Children learn to see before they learn to grab, and to grab before they learn to plan and handle the unexpected.

Perception comes first. Manipulation follows. More complex responsibilities come after that. At every stage, the robot must earn the next job by doing its current one well enough.

Before asking a robot to pick up a sock, we wanted it to understand where it was, where the sock was, and how to reach it.

Most of the industry started at the top, with humanoids. We started at the bottom, with a robot whose job is to see and move through a home precisely with 1cm accuracy in any lighting condition.

Floor cleaning gave that foundation an immediately useful job. It forced us to confront navigation, clutter, privacy and everyday reliability before reaching for more complex chores.

The floor cleaner isn’t a detour from our larger ambition. It is how we’re building toward it.

4. The 99.999% rule in robotics

At 90%, one in ten decisions is wrong, and a robot makes thousands in a single clean. That's the robot that bumps, gets lost, and falls down the stairs.

Every extra nine is a new mountain. The failures get rarer, harder to find, and exponentially harder to fix. They barely even happen until they happen in your home.

Matic's visual SLAM runs at 99.999% in 16K+ homes. We’re the ONLY unsupervised home robot at scale with pure vision-only full autonomy. If you ask us, the gap between 80% and 99.999% is where our 9 years of engineering went.

We close that gap inside real homes. When Matic handles something imperfectly, it saves a short clip and keeps it on the device. It only leaves if the family chooses to share it. If they do, it gets labeled, fed back into the model, and every Matic gets smarter, including theirs.

Families control what leaves their homes. We do the work of making the product better.

Better robots earn trust > trust brings more homes > and more homes teach the robot more.

5. Where Matic is going next

Phase one was perception and it's nearly done. Matic has covered 500 million square feet, 400K miles in thousands of real lived-in homes.
Now phase two is going to be about manipulation. And our idea is to build a robot that doesn't just move through your home, but acts in it to eliminate even more chores.

Each step must be useful today, not justified by something we promise tomorrow. The evolution of Matic is the revolution.

The goal isn’t to put the most impressive humanoid in your living room.

It’s giving your family time and energy back through robots that earn your trust, protect your privacy, and help without becoming another responsibility.

More time for each other. Less work getting in the way.

That’s Matic.
Get yours today at https://t.co/tEo81BKSmA