Local darzi —-> readymade garments —-> designer darzi
TECHNOLOGY
-
NLP Cross-Field Engagement Declined Significantly Since 1980
By
–
10/ The Influence Between NLP and Other Fields – aims to quantify the degree of influence between 23 fields of study and NLP; the cross-field engagement of NLP has declined from 0.58 in 1980 to 0.31 in 2022…
-
Knowledge Capacity Scaling Laws in Language Models
By
–
8/ The Physics of Language Models – investigates knowledge capacity scaling laws where it evaluates a model’s capability via loss or benchmarks, to estimate the number of knowledge bits a model stores.
-
AI and Metaverse: Unlocking New Opportunities Together
By
–
Virtual worlds of the Metaverse could exist without AI. However, combining AI and Metaverse can unlock new opportunities, as evident in the following use cases. Source @101Blockchains Link https://
bit.ly/49r9R98 via @antgrasso #Metaverse #AI -
PyTorch Performance Improvements with Nightly Build and Optimizations
By
–
THE REVENGE OF PYTORCH
just kidding 🙂 @cHHillee (from PyTorch team) was kindly able to help improve the PyTorch baseline, done by 1) upgrading to nightly, 2) using the "compound" F.sdpa (scaled dot product attention) layer directly, and turning on a torch compile flag: -
AWS reliability advantage: 15-year track record stability matters
By
–
That's one of AWS's biggest advantages in my mind – they have about a 15 year track record of not breaking stuff Anyone else who wants to build up that kind of track record needs to spend 15 years doing it
-
AWS Reliability and Product Trust in Cloud Computing
By
–
Yeah that's true, AWS are uncommonly good at keeping their stuff working – not just boto3 but all of their AWS products in general I don't trust anyone else though!
-
API Documentation: JSON Specs Over Client Libraries
By
–
Request for model API providers: please put JSON API docs (with example curl commands) somewhere prominent I always look for those first, before client libraries, because my experience is that client libraries are more likely to have backwards incompatible breaking changes
-
PyTorch Optimization: torch.compile vs Vanilla Performance
By
–
this isn’t comparing to torch.compile, which is the torch-native optimized version, it’s comparing to vanilla pytorch which is notoriously bloated and slow 🙂
-
ONNX WebAssembly Trade-offs in AI Model Deployment
By
–
i’m very skeptical that that’s a better decision than just using onnx wasm or whatever else is available