The sages disagree on this question, but it seems to me that not only the absence of goodness but also its inversion exists, in ways that are not simply directed on an alternate conception of goodness or how to achieve it
RESEARCH
-
Decision Transformer Learns Game Instructions from Multimodal Input
By
–
Read to Play (R2-Play): Decision Transformer with Multimodal Game Instruction Jin et al.: https://
arxiv.org/abs/2402.04154 #ArtificialIntelligence #DeepLearning #MachineLearning -
Superstition Versus Epistemology: Knowledge Models and Confidence
By
–
Superstition is belief that violates epistemology, it erases the boundary between knowledge and fantasy. It is generally necessary to maintain effective models in the absence of available rational justification. Such models deserve no confidence in their factuality though.
-
Images from Noise: Quantum Emergence in AI Generation
By
–
images arising from noise like life emerging from quantum foam
-
Reflecting on the future of ML abstraction
By
–
How far are we from ML abstraction over other ML abstractions?
-
ML Abstraction Design: Balancing Current Practice and Future Innovation
By
–
ML abstraction design is hard in part because progress is made by people breaking through the existing abstractions. So must write code that facilitates the way things are done today while also making it easy to try out new ideas of how things could be done tomorrow.
-
Cerebras Leads AI Semiconductor Startups in Research
By
–
Cerebras overtakes peers as #1 AI Semiconductor Startup In the freshly-updated 2023 State of AI Report Compute Index from Air Street Capital and Zeta Alpha, Cerebras is highlighted for leading all AI semiconductor startups in research publication counts, open source
-
AI Uncovers Historical Secrets From Lost Ancient Documents
By
–
Excellent research breakdown, as usual. Can't wait to see what AI can uncover about our past from "lost" documents and scrolls.
-
RAG Approach: Combining Generative Models with Retrieval Systems
By
–
RAG is an umbrella term for combining a generative language model and a retrieval system. @PSH_Lewis, Manager of Technical Staff in RAG at Cohere, explains our approach to building RAG models in the video below. Check it out! pic.twitter.com/fko1ac6Pn3
— Cohere (@cohere) 11 février 2024RAG is an umbrella term for combining a generative language model and a retrieval system. @PSH_Lewis
, Manager of Technical Staff in RAG at Cohere, explains our approach to building RAG models in the video below. Check it out! -
Neural Operators Mixed Precision Training Achieves 50% Throughput Gain
By
–
Super excited to share our paper on efficient training of Neural Operators with mixed precision, recently accepted at #ICLR2024! We show more than 50% gain in throughput with almost no loss in accuracy. Neural operators are #AI methods for solving #PDE . Unlike traditional