In 2013, a group of makers got together to find new ways to work together. A lot has happened since. We recently celebrated our 10th birthday :). Over the years, we've had the privilege of working with some exceptional organizations and doing work we're proud of. 1/2

RT @theOnlyMaDDogx: 1/ @AtharvaRaykar sharing lessons learnt from taming complexity while building real-time voice AI applications. We're t….

RT @AtharvaRaykar: rage against the complexity.

RT @fifthel: And the cookies are here! Thank you team @nilenso for sponsoring cookies and coffee/tea for participants. .

RT @fifthel: Workshop curated by @AtharvaRaykar and @yashgandhi with review feedback k from @lavanyats @harshad_geek.

RT @fifthel: Today’s workshops came with a sweet surprise 🍪.Big thanks to our sponsor @nilenso for the delicious deal - the cookies were al….

RT @theOnlyMaDDogx: 3/ And you couldn't miss these cookies during the chai break, powered by the good folks at @nilenso, even if you tried….

RT @fifthel: Ooh ooh. Overhead that @_svs_ has reserved a seat (and a chai cuppa & cookie courtesy @nilenso) at the 2025 edition too. Age….

RT @AtharvaRaykar: Voice bot development demands scientific methods and not just engineering blueprints. I will talk about what engineering….

RT @vedang: Everyone seems to say you should do Evals, but no ones tells you how. Do you want to know how to do Evals properly? Attend th….

He's also compiled all the specific people mentioned in this blog into a list.

Here is the post:.

There's a lot of links, with descriptions on what kind of information he gets from each source. And some example articles from each source. Atharva does not chug water from a firehose.

He identifies information sources of different types:.- starting points to learn the basics and understand frontier capabilities.- practitioners figuring out how engineering is changing in the face of AI.- news about the industry at large, research at the frontier etc.

Keeping up with AI progress can be overwhelming and surprisingly hard. @AtharvaRaykar writes about where he finds signal in this noisy landscape.

RT @BkosiAm: Enjoyed reading about how to continue learning while using AI Agent tools like Cursor:

RT @AtharvaRaykar: I was seeing @karpathy's Software 3.0 talk, as one should. Surreal to see him recommend my writing to make a point on A….

Read more here:.

Quantization is a tradeoff between response times and accuracy. Measured on a subset of easy Text-to-SQL tasks.

How good are small LLMs that run on consumer hardware for practical tasks?. How are they affected by model size and quanitization?. @yogirajhendre put them to the test. Turns out, they can be quite capable, even if they fall behind their large frontier counterparts.

RT @AtharvaRaykar: The endorsement from @simonw has been hugely validating <3. I've been messing with a bunch of workflows for a while, and….