Nicolay Gerold

In the digital world, self-nudging aims to empower people to be citizen ‘choice architects’ by designing their informational environments in ways that work best for them and that constrain their activities in beneficial ways. We can, for instance, remove distracting and irresistible notifications. We may set specific times in which messages can be... See more

dstack is an open-source toolkit and orchestration engine for running GPU workloads. It's designed for development, training, and deployment of gen AI models on any cloud.

Supported providers: AWS, GCP, Azure, Lambda, TensorDock, Vast.ai, and DataCrunch.

Latest news ✨

• [2024/01] dstack 0.14.0: OpenAI-compatible endpoints preview (Release)


• [2023/12] dst

... See more

Let’s clarify by sharing the before-and-after (delta) and tying it to team goals.

✅ Impact: Cut home page load time by 66%, from 3 seconds to 1 second through additional caching. This resulted in a 30% increase in engagement, accounting for more than half of our quarter OKR target.

The Semantic Layer

for every data app

Connect data silos, drive consistent metrics, and power your AI and analytics with context.

When you are very alert, everything is a stimulus, you are very unlikely to suppress an action. You should suppress all incoming stimuli except the one you want to focus on. Best situation for learning is silence. If you are tired, some background noise can increase alertness.

Include a down regulation after your workouts (longer exhale). 5 min after workouts (e.g. in the shower), 1 min after important parts of your workouts.

🥤 Cola [NeurIPS 2023]

Large Language Models are Visual Reasoning Coordinators

Liangyu Chen*,†,♥ Bo Li*,♥ Sheng Shen♣ Jingkang Yang♥

Chunyuan Li♠ Kurt Keutzer♣ Trevor Darrell♣ Ziwei Liu✉,♥

♥S-Lab, Nanyang Technological University

♣University of California, Berkeley ♠Microsoft Research, Redmond

*Equal Contribution †Project Lead ✉Corresponding Author... See more

To train LLMs, you need data that is:

Large — Sufficiently large LMs require trillions of tokens.

Clean — Noisy data reduces performance.

Diverse — Data should come from different sources and different knowledge bases.

What does clean data look like?

You can de-duplicate data with simple heuristics. The most basic would be removing any exact duplicates... See more

Navigating the terrain of vector databases in 2023 reveals a diverse array of options each catering to different needs. The comparison table paints a clear picture, but here's a succinct summary to aid your decision:

... See more