Issue 1: New AI Regulations, Twitter Bot for Trending ML Research
Welcome to the very first issue of The Comet Newsletter. We’re excited to bring you the best machine learning content the internet has to offer—and perspective from our experts in the field. Stay tuned for future issues, as we have big things planned.
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INDUSTRY | WHAT WE’RE READING | PROJECTS | OPINION
Huma, which uses AI and biomarkers to monitor patients and for medical research, raises $130M
UK based Huma’s digital phenotyping and biomarker capabilities provide a more comprehensive, objective, and continuous picture of human function in health and disease.This past year, the company has partnered with the NHS to help remotely manage patients diagnosed with COVID-19 by tracking symptoms, vital signs, and deterioration, via a virtual ward.
“Huma can pick up data that patients contribute via smartphones, or by way of diagnostic devices that measure glucose, blood pressure or oxygen saturation, and the plan will be to use the funding to augment that in a couple of ways: to continue investing in R&D to both expand the kinds of biomarkers that Huma can measure and to work on more research and trials; to continue expanding London-based Huma’s business particularly in newer geographies like the US”
“The whole idea is how to decentralize care and research.”
- Dan Vahdat, CEO and Founder.
INDUSTRY | WHAT WE’RE READING | PROJECTS | OPINION
New AI Regulations Are Coming. Is Your Organization Ready?
“For companies adopting AI, the dilemma is clear: On the one hand, evolving regulatory frameworks on AI will significantly impact their ability to use the technology; on the other, with new laws and proposals still evolving, it can seem like it’s not yet clear what companies can and should do.”
INDUSTRY | WHAT WE’RE READING | PROJECTS | OPINION
Twitter Bot that Tweets Trending ML Papers
The current pace of Machine Learning Research is overwhelming. Reddit user u/naritaairport has created a Twitter Bot that helps you keep up with trending research.
How to 10X throughput when serving Hugging Face models without a GPU!
Our own Jacques Verre shows how, in less than 50 lines of code, you can deploy a BERT-like model from the Hugging Face library and achieve over 100 requests per second with latencies below 100 milliseconds for less than $250 a month.
INDUSTRY | WHAT WE’RE READING | PROJECTS | OPINION
Rethinking Larger Conferences
AI is an ever-expanding, interdisciplinary field. From different areas of study (vision, language, robotics, etc) to endless industry verticals and use cases (manufacturing, automotive, retail, etc.), it’s nearly impossible to consolidate all of a year’s AI developments into a single conference. In this recent blog post, Julian Togelius makes the compelling argument that, when it comes to AI conferences that aim to truly build connections and community, bigger isn’t always better:
“These conglomerate conferences are supposed to be the top venues for technical work in each sub-field, so presenters are mostly addressing the 3% of conference attendees that work on the same topic….For someone new to the community, it certainly seems that a smaller conference where people may actually notice you standing alone by the wall and go up and talk to you would be a much better opportunity to get to know people. Basically, a conference with thousands of attendees does not provide community.”
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