Vaultic Ventures

[VraserX e/acc @VraserX]

Ray Kurzweil is basically the modern Nostradamus of technology.

People mocked the exponential curves, the timelines, the confidence.

Then reality started catching up.

He saw where computing was going long before most people even understood the game.

[MIT CSAIL @MIT_CSAIL]

What a difference 70 years makes: 3.75 MB in 1956 & 1 TB today.

v/@JonErlichman

[Enezator @Enezator]

I don’t even want to think about how far artificial intelligence will go in a few years

[Adi Oltean @AdiOltean]

We have just used the @Nvidia H100 onboard Starcloud-1 to train the first LLM in space!

We trained the nano-GPT model from Andrej @Karpathy on the complete works of Shakespeare and successfully ran inference on it.

We have also run inference on a preloaded Gemma model, and we plan to try more exciting models in the future.

Getting the first H100 to work in space required a lot of innovation and hard work from the incredible Starcloud team to make this breakthrough.

This is a significant first step toward moving almost all computing off Earth to reduce the burden on our energy supplies and take advantage of abundant solar energy in space! 🚀

[Deedy @deedydas]

Valve, the makers of Steam, Half-Life and CounterStrike, made ~$17B in revenue this year with ~336 employees.

That's >$50M per employee, the highest for any (non-crypto) company in the world. The average pay is ~$1.3M/person.

One of the most efficient businesses of all time.

[Microsoft Events @events_msft]

Tomorrow #MSIgnite kicks off the next wave of AI transformation. ⚡️🌐

Join us live at 9AM PT as Microsoft leaders unveil what's next in AI, cloud, and security.

Save this post and tune in: https://t.co/dmkTnwuTvB

[Satya Nadella @satyanadella]

Today we announced our new Fairwater datacenter in Atlanta, connected with our first Fairwater site in Wisconsin and our broader Azure footprint to create the world’s first AI superfactory.

Fairwater exemplifies our vision for a fungible fleet: infra that can serve any workload, anywhere, on fit-for-purpose accelerators and network paths, with maximum performance and efficiency.

AI workloads have evolved beyond large-scale pre-training. Today, they encompass fine-tuning, reinforcement learning (RL), synthetic data generation, evaluation pipelines, and more. Fairwater is built to support this full lifecycle:

Max density: Fairwater’s two-story design and liquid cooling system lets us place racks in three dimensions and pack them with GPUs as densely as possible, minimizing cable runs and improving latency and effective bandwidth.

Fleet: Each Fairwater DC can integrate hundreds of thousands of the latest NVIDIA GPUs into a single coherent cluster. This provides flexible infra that can support the full spectrum of workloads, and ensure no GPU is left unnecessarily idle.

And that’s on top of the more than 100,000 GB300s coming online this quarter alone for inference across the rest of our fleet. For us, it’s all about turning every gigawatt into the maximum number of useful tokens. Not every GW is created equal!

Planet-scale: Every Fairwater DC will connect through our continent-spanning AI WAN to prior generations of AI supercomputers, forming a truly fungible pool of compute. This enables developers to scale beyond the capacity of a single site and dynamically land workloads on the right infra for their needs.

Together, these innovations let us bring together different generations of silicon and AI systems across DCs and geos into a single elastic system that scales seamlessly across training and inference workloads

And this elastic AI capacity is all available alongside all the other cloud services (compute, storage, databases, app services) that AI agents and workloads need.

This is what we mean when we talk about building a fungible fleet – a single, unified platform that pushes the limits of performance per watt and per dollar.

Read more: https://t.co/PsMoTN3UPQ

[Georgia Channing @cgeorgiaw]

🔥 It's here: OpenFold3 is now live.

THE open-source foundation model for predicting 3D structures of proteins, nucleic acids & small molecules. This is where the future of drug discovery and biomolecular AI lives.

Built by @open_fold. Hosted on @huggingface.
👇 more

[Brett Adcock @adcock_brett]

Introducing Figure 03

[Justine Moore @venturetwins]

I love whatever is wrong with this viral AI companion named Merv

[Brett Adcock @adcock_brett]

For the first time, a humanoid robot can fold laundry using a neural net

We made no changes to the Helix architecture, only new data

[Tivadar Danka @TivadarDanka]

Differentiation reveals much more than the slope of the tangent plane.

We like to think about it that way, but from a different angle, differentiation is the same as an approximation with a linear function. This allows us to generalize the concept.

Let's see why:

[Anjney Midha @AnjneyMidha]

in the last 35 days, @OpenAI codex has merged 345,000 PRs on github.

345,000.

AI is eating software engineering

[Bojan Tunguz @tunguz]

Interesting point.

[Min Choi @minchoi]

This is wild!

ByteDance's Goku+ AI turns text into hyper-realistic ad videos, cutting costs by up to 99%!

Ads will never be the same.

10 wild examples:

[Min Choi @minchoi]

This is wild.

Humanoid robots can now copy elite athletes and dance movements using ASAP (Aligning Simulation and Real Physics), an AI framework presented by CMU researchers and NVIDIA.

10 wild examples:

1. APT Dance

[Min Choi @minchoi]

We are done for.

Robots are now shopping with you, walking, running, and even dancing.

10 wild examples:

1. Shopping with robot and robot dog in Milano

[Massimo @Rainmaker1973]

Fruit farmers' most difficult task is organizing the harvest. Tevel's drones select, pick and box only ripe fruits with the help of an AI
https://t.co/uiksOSPnKD

[internet hall of fame @InternetH0F]

How much faster pit stops got from 1990 compared to 2023 is wild

[Elon Musk @elonmusk]

Precisely