Enjoyed discussing #QuantumComputing in the automotive industry at the Bitkom #QuantumSummit24 exploring application areas from material science, simulations, quantum machine learning to optimization. Check out my talk: https://t.co/5SDKYPsk36 ##AIDAQ
The Transformer is a magnificient neural network architecture because it is a general-purpose differentiable computer. It is simultaneously:
1) expressive (in the forward pass)
2) optimizable (via backpropagation+gradient descent)
3) efficient (high parallelism compute graph)
Glad to see this work finally coming out: Together with some 100+ of the best scientists from national labs, universities and companies around the globe, we define a vision for quantum-centric supercomputing in Materials Science.
https://t.co/B8WYp5bK0h
https://t.co/Bb8Zg7dP2D
Probably the best 1h introduction to LLMs that I've seen. And after 20mins its not an introduction, its getting into cutting edge research updates updated up to this month. I had not heard of the data exfiltration by prompt injection or the recent finetuning Poisoning attacks.
🪩The @stateofai 2023 is now here.
Our 6th installment is one of the most exciting years I can remember. The #stateofai report covers everything you *need* to know, covering research, industry, safety and politics.
There’s lots in there, so here’s my director’s cut 🧵
1/3 Clarke’s three laws: 1. When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong.
Just released! The #AIIndex2023 rounds up the latest trends in AI. This year’s report introduces more original data than any previous edition, a new chapter on AI public opinion, and more. Here are the top takeaways: ↘️ https://t.co/3qpNc2aOG9