Ella
34 posts
@hc_ella
ai research × product @ stealth 💫 prev: codegen @Bloomberg / 🤖🚗 @StanfordAILab @SISLaboratory Lyft L5 (@Woven_Toyota) / ML @GoogleAI @Meta
Larry Ellison $ORCL highlighted something critical: models like ChatGPT, Gemini, Grok, and Llama are all trained on largely the same public internet data. When everyone trains on the same information, models inevitably converge. That’s why AI is moving toward commoditization. The real moat isn’t the model itself. It’s the proprietary data behind it. Companies that can train on exclusive datasets gain an advantage competitors can’t replicate. Having data that no one else has will allow you to dominate your market.
When the cost of code goes to zero, marketing is your only advantage. Introducing Flint. It builds you a unique page for every ad, keyword, and customer. We’re already doubling conversions for @Cognition and @Graphite. Sign up at @tryflint.
A team of researchers from Bloomberg’s #AI Engineering group introduced PExA, an #agenticAI framework that achieved 70.2% execution accuracy on the Spider 2.0 leaderboard, one of the most demanding benchmarks for #text2sql generation bloom.bg/4af28yB #CodeGeneration (1/2)
Researchers from @Bloomberg's #AI Engineering Group co-authored 4 papers at @emnlpmeeting in Singapore this week; learn more about their research, why the results are notable, and how their work will advance the state-of-the-art in #nlproc bloom.bg/3GTbK2p #EMNLP2023
Researchers/engineers from our #AI Engineering Group are co-authors on 4 papers at @aaclmeeting this week; learn more about their #NLProc research, why the results are notable, and how their work will advance the state-of-the-art in #NLProc bloom.bg/3XjNsFr #AACL22
(2/4) Congrats to Ella Hofmann-Coyle, Mayank Kulkarni, Jane Xie, @gtcomputing’s Mounica Maddela (@mmaddela1005), & @Daniel_Preotiuc for having their paper “Extractive Entity-Centric Summarization as Sentence Selection using Bi-Encoders” accepted for #aacl22
