Joyce J. Shen (Page 10)

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What does it take to lead early-stage investments?

Venture investing in the early stage is not for the faint of heart. It takes a lot of strategic and operational work to achieve key business and financial milestones which are prerequisite for growth equity. No one can do all the work alone. In fact, it requires the right type

Joyce’s picks: readings in ML/AI , August 18, 2023

Spotify launched Confidence — an experimentation platform: blog and sign up for private beta. (link) “AI chatbot K Health picks up $59M in fresh funding, inks partnership with Cedars-Sinai” (link) “A New Frontier for Travel Scammers: A.I.-Generated Guidebooks” (NYT) “The case for and against open-source large language models for

Building a cyber defense fortress

Cyber attacks are getting out of hand, and every organization is vulnerable. Just looking at recent news: Clorox had to take certain operations offline due to cyber attack (Reuters) Discord went offline because over 700K user information were stolen (link) Prince George's County public school system was hacked

The Discipline of Business Updates

Sharing regular business updates is an important discipline for startups and management teams. For me, these regular updates come each week and month in the forms of weekly CEO calls and email updates from CEOs. These regular updates focus on the state of the business - finance, sales, marketing, product,

Joyce’s picks: readings in ML/AI, July 28, 2023

“Aided by A.I. Language Models, Google’s Robots Are Getting Smart” (NYTimes) “AI search of Neanderthal proteins resurrects ‘extinct’ antibiotics” (Nature) “SK Hynix and Samsung’s early bet on AI memory chips pays off” (FT) “KNN-Diffusion: Image Generation via Large-Scale Retrieval” (Link) “Consistency Models” (Link) “SelfCheckGPT: Zero-Resource Black-Box Hallucination

Generative AI x Knowledge Graphs

Data wrangling tasks include data acquisition, data ingestion, data extraction, data cleaning, data transformation, exploratory data analysis, and data pipelining for ML tasks. Data variety, dimensionality, complexity, duplication, provenance can further complicate this data wrangling process.

Joyce's picks - readings in machine learning /AI - July 21, 2023

Meta LLaMA — original blog (link) Meta and Microsoft Introduce the Next Generation of Llama (link) Most outsourced coders in India will be gone in 2 years due to A.I., Stability AI boss predicts (CNBC) One senator’s big idea for AI (Politico) Unstructured, which offers tools to prep enterprise

Joyce’s picks — readings in machine learning /AI

July 14, 2023 Nvidia deepens bets on AI in drug discovery with Recursion investment (Reuters) New York City’s AI Hiring Bias Law Creates Hurdles for Companies (Bloomberg Law) Removing bias in AI: Wells Fargo shares open toolkit for explainability (Venturebeat) This amazing new AI tool turns a scribble into

Bigger is not better in machine learning

I heard an interview today featuring the Chief Scientist of Mosaic ML. One of the things Jonathan Frankle said is that bigger is not better. He, of course, is talking about machine model size (e.g., number of parameters). I posit that we can agree that bigger models may not

Cheerleaders and Advocates

Some of the best emails and texts arrived in my inbox in the last few days were from friends and former students informing me that the small part I played in helping them made a difference in their professional endeavors. Here is an example I got this Sunday morning, and