Next year we’ll see the rise of hybrid capabilities, model-driven businesses and the demand for GPUs. Our CEO Nick Elprin is sharing his predictions for 2023 with @BigData_Review
: https://
domino.buzz/3GkmZ2O #datascience
RESEARCH
-
Hybrid AI Capabilities and GPU Demand Predictions for 2023
By
–
-
Artificial Intelligence Marks Breakout Year in Technology
By
–
A breakout year for artificial intelligence
#RuleoftheRobots #AI -
First Paper Using LangChain Framework Published
By
–
The first paper (that we know off) to use @langchain
! @johnjnay -
Security Paper Review Process Demands Increased Burden Reviewers
By
–
Besides the fact Im getting older, some reasons last year was more tiring:
– security papers are long! 13 two-column pages (vs 8 in ML)
– also, their revision process requires more commitment from reviewers
– more generally, labour expected from reviewers per paper is on the rise -
NLP and Quantum Computing Drive Financial Innovation
By
–
#NLP & #quantum computing could drive years of new financial innovation, says @NVIDIAAI
's Mark J. Bennet. Could 2023 be the first year for you? Find out how in the Finance and Insurance #DataScience Innovator's Playbook https://
domino.buzz/3X8GNgH #MLOps -
Chinchilla’s implications: Dataset size over model size in LLMs
By
–
Great post (5mo ago) "chinchilla's wild implications" giving context to LLM goldrush shifting from model size to dataset size following Chinchilla https://
lesswrong.com/posts/6Fpvch8R
R29qLEWNH/chinchilla-s-wild-implications
…
Subtle important detail: analysis assumes 1 epoch. Recent work (e.g. Galactica) gives hope for 1+ regime. -
Subtle AI Watermarking in Inter-Token Frequency Distributions
By
–
The watermark Aaronson proposed is much more subtle than that, and isn't detectable within a text editor. The watermark exists only in the inter-token frequency distributions, and can't be checked without complicated code.
-
OpenAI founding anniversary: seven years milestone
By
–
the first day of openai, seven years ago today
-
Tracing GPT-3.5’s Emergent Abilities to Their Sources
By
–
GPT-3.5 is technically all of the following, but I meant it as just the first three:
– code-davinci-002
– text-davinci-002
– text-davinci-003
– ChatGPT See here: https://
yaofu.notion.site/How-does-GPT-O
btain-its-Ability-Tracing-Emergent-Abilities-of-Language-Models-to-their-Sources-b9a57ac0fcf74f30a1ab9e3e36fa1dc1
… -
Language Models and Mathematical Accuracy: Parameters vs Hard Numbers
By
–
Parameters are great. Absolutely agree. For hard numbers, though, the language model doesn't do math in the way you'd expect. Often it'll be off on those, but they will get it closer to the goal you're seeking.