Matt Clifford

matthewclifford.com

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Co-founder & CEO, Entrepreneur First @join_ef http://joinEF.com Co-founder & NED @codefirstgirls Newsletter: http://tib.matthewclifford.com Podcast: http://tib.buzzsprout.com

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Tweet May 5, 2023

This leaked google memo is a great overview of what open source AI has achieved... but the conclusion is wrong. twitter.com/jordnb/status/1654496023778131970/photo/1 twitter.com/simonw/status/1654158105221922816

by Jordan Burgess

Recommended by 1 person

1 mention by Matt Clifford

Tweet Apr 24, 2023

Can a new transformer architecture with 2 million 🚀 tokens fix the token window problem? Or are there no free lunches? What do we gain, what do we give up? New paper from @MikhailBurtsev, Aydar Bulatov and @yurakuratov Let's break it down👇 arxiv

by Hrishi Olickel

Recommended by 1 person

1 mention by Matt Clifford

Paper Apr 19, 2023

Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models

by Pan Lu and 4 others

Recommended by 1 person

1 mention by Matt Clifford

Article May 28, 2020

The Scaling Hypothesis · Gwern.net

by Gwern

Recommended by 2 people

1 mention by Matt Clifford

Article Apr 14, 2023

Prompt injection: what’s the worst that can happen?

by Simon Willison

Recommended by 1 person

1 mention by Matt Clifford

Tweet Apr 15, 2023

Reading through the Segment Anywhere Model (SAM) paper, some notes & insights as I do so in this Twitter thread. This whole paper is quite incredible actually, very strong work 1/n arxiv.org/pdf/2304.02643.pdf

by Brad Neuberg

Recommended by 1 person

1 mention by Matt Clifford

Tweet Apr 14, 2023

Recent report on China's chip capabilities, recommended. TL;DR: in trailing-edge chips (20-120 nm) chips, China leads or has a good odds of self-sufficiency; in leading-edge (phones, AI), seems very unlikely they can suceed or go self-sufficient

by Will

Recommended by 1 person

1 mention by Matt Clifford

Article

We must slow down the race to God-like AI

by Ian Hogarth

Recommended by 2 people

1 mention by Matt Clifford

Tweet Apr 9, 2023

This thread is an incredible insight. Because we trained GPT on code, it means we’ve trained it on billions of individual micro-logical predicate sequences, so it “knows” logic by thinking in code. twitter.com/Mihoda/status/1644564637420249088

by Yishan

Recommended by 1 person

1 mention by Matt Clifford

Article Mar 28, 2023

From Deep to Long Learning?

by Dan Fu and Michael Poli

Recommended by 1 person

1 mention by Matt Clifford

Tweet Apr 6, 2023

We wrapped up the first LLM hackathon for applications in materials and chemistry last week. The results to me were astounding. We are at the point now where some tasks that took years can now be completed in days. Here is a list of the fantastic sub

by Ben Blaiszik

Recommended by 1 person

1 mention by Matt Clifford

Tweet Apr 6, 2023

This graph from the GPT-4 tech report is a much bigger deal than most people seem to have realised. I think it allows us to predict with reasonably high confidence that the problem of LLM's making things will be quite easy to solve. Here's why: twi

by Raza Habib

Recommended by 1 person

1 mention by Matt Clifford

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