INNOVATION - AI Dynamics

Steamship Simplifies AI App Development and Deployment

By

@sumanth_077

–

22 February 2023 5h39

Thanks for Sharing Rohit. @GetSteamship makes it really easy to develop and deploy AI Apps.

→ View original post on X — @sumanth_077

22 February 2023

German AI startup Aleph Alpha claims 300-billion parameter LLM Luminous-World

By

@aibreakfast

–

22 February 2023 3h28

German AI startup @Aleph__Alpha claims it will have a 300-billion parameter Large Language Model "Luminous-World" trained this year for “highly complex and critical applications” (GPT-3 has 175 billion parameters)

→ View original post on X — @aibreakfast

22 February 2023

Generative AI Competition Set to Intensify

By

@_ganeshp

–

22 February 2023 1h20

I have a feeling the gloves are going to come off in this generative AI race!

→ View original post on X — @_ganeshp

22 February 2023

Google UCLA Discover Lion Algorithm for DNN Optimization

By

@jiqizhixin

–

22 February 2023 1h03

Google & UCLA Formulate Algorithm Discovery as Program Search, Yielding ‘Lion’ for SOTA DNN Optimization https://
syncedreview.com/2023/02/21/goo
gle-ucla-formulate-algorithm-discovery-as-program-search-yielding-lion-for-sota-dnn-optimization/
…

→ View original post on X — @jiqizhixin

22 February 2023

Google Researchers Advance Natural Sciences Beyond Computer Science

By

@googleai

–

22 February 2023 0h36

Google researchers are exploring more than just the realms of computer science. Today we discuss some of the other exciting advances and discoveries we’ve made in the natural sciences, from biology to quantum physics. Read more at https://
goo.gle/3XSdizt

→ View original post on X — @googleai

22 February 2023

Part 7: Quantum Computing Advances in Natural Sciences Research

By

@jeffdean

–

22 February 2023 0h30

Part 7 is out, posted by @johnplattml on behalf of many, covering advances in our work on various problems in the natural sciences, including neurobiology, biochemistry, and the application of quantum computing to problems in physics.

→ View original post on X — @jeffdean

22 February 2023

ControlNet Paper: A Deep Learning Enthusiast’s Dream Abstract

By

@dotcsv

–

22 February 2023 0h27

El abstract del paper de ControlNet parece una carta a los reyes magos de cualquier fan del Deep Learning

→ View original post on X — @dotcsv

22 February 2023

Robots Learn Natural Language Communication and Real-World Skills

By

@jeffdean

–

22 February 2023 0h26

Part 6 in the series is out, discussing our work in robotics, especially allowing robots & humans to communicate naturally via language, apply common sense knowledge in real-world situations & increasing the number of low-level skills robots can perform.

→ View original post on X — @jeffdean

22 February 2023

Part 5: Scalable Algorithms, Privacy, and Causal Inference

By

@jeffdean

–

22 February 2023 0h25

Part 5 in the series is out, posted by @Mirrokhni on behalf of many, covering advances in:
· Scalable algorithms (esp. for graphs and clustering)
· Privacy and federated learning
· Market algorithms & causal inference
· Algorithmic foundations and theory

→ View original post on X — @jeffdean

22 February 2023

GTC23 Conference Features Jensen Huang Keynote on Generative AI

By

@nvidia

–

22 February 2023 0h00

GTC is making headlines! Join us March 20-23 for a news-packed keynote from founder and CEO Jensen Huang and sessions covering the latest advancements in #generativeAI, the #metaverse, robotics, cloud computing, and more. Register for free today. #GTC23 https://
nvda.ws/3lUBxzO

→ View original post on X — @nvidia

22 February 2023