Matt Rubashkin

Science, Ultimate, & Blraps

[Berke Buyukkucak @berkebuyukkucak]

🎤 This week, we sat down with @mrubash1, the Head of Eng at @FutureHouseSF for Superbio Scientist Spotlight. https://t.co/8EpWpIKSCH

It was so inspiring to talk to such an optimistic, ambitious, and thoughtful technologist who urged us to stay curious:

"The world has really never been more of an oyster for folks that want to dive in than right now."

[Sam Rodriques @SGRodriques]

Today, Future House is announcing WikiCrow, our first automated system for synthesizing scientific knowledge. As a demo, we are releasing a cited technical summary for every gene in the human genome that previously lacked a Wikipedia article: 15,616 in all.

As scientists, we stand on the shoulders of giants; but most scientific knowledge today is still locked up in impenetrable technical reports. One of the ways AI will help to accelerate science is by enabling us to rapidly synthesize existing scientific knowledge. WikiCrow generates Wikipedia style articles on scientific topics by summarizing full-text scientific articles that we can access through our academic affiliations. In the past few days, we used WikiCrow to generate high quality, cited summaries for all 15,616 protein-coding genes that previously lacked high-quality Wikipedia articles, with information sourced from over 14 million pages of more than 850,000 relevant papers. WikiCrow is much more reliable than human authors at providing citations for information, and makes inaccurate statements about 9% of the time. We don’t usually observe hallucinations, but the model sometimes confuses gene names and details like the N and C terminus. We expect these errors to become rarer as we mature our systems. As they do, resources such as these will make it easier for researchers to understand and contextualize the results of their experiments, and will be a key resource for the AI Scientists we build in the future.

The articles are hosted on our website. Read our blog post here: https://t.co/GSRT3tkpU8

and read our paper on PaperQA, the underlying agent, here: https://t.co/5FhQMRq0nL

[Sam Rodriques @SGRodriques]

Today, we are announcing Future House, a philanthropically-funded moonshot focused on building an AI Scientist.

At Future House, our 10-year mission is to build semi-autonomous AIs for scientific research, to accelerate the pace of discovery and to provide world-wide access to cutting-edge scientific, medical, and engineering expertise. We have chosen to focus on biology because we believe biology is the science most likely to advance humanity in the coming decades, through its impact on medicine, food security, and climate. We also believe that biology research is set to scale, and AI will help us get there.

Future House is an independent, non-profit research organization, headquartered in San Francisco. At Future House, biology researchers and AI researchers will work together to build AI Scientists and to use those AI Scientists to make research 10x to 100x faster than it is today. We are fiercely committed to a flat structure, team science and individual contributions. We are also hiring, for AI researchers, wet lab biology researchers, and other roles. If this mission and these ideas are exciting to you, get in touch. Join our mailing list, follow us at @FutureHouseSF, and reach out to us at [email protected].

For more information, read our blog post here: https://t.co/drN0rY5WU2

and check out the @Bloomberg feature here: https://t.co/jIjela6b9L

[Matt Rubashkin @mrubash1]

Mind Blown - Art generated in 5s with @OpenAI's DALL-E model #ai #art

[Matt Rubashkin @mrubash1]

I'm excited to be building the Future of Healthcare with Ready: https://t.co/hlaAqQHhLZ

[Matt Rubashkin @mrubash1]

@googlefi Please reach out via dm

[Matt Rubashkin @mrubash1]

@googlefi I was incorrectly denied my Moto G Refund, and believe you are doing this to other Google Fi Customers :(

1. I used the motoG as a data only sim
2. Then added the motoG phone to my account with full Fi service (which was recommended by the last customer)

Help?

[Matt Rubashkin @mrubash1]

@googlefi
I was incorrectly denied my Moto G Refund, and believe you are doing this to other Google Fi Customers :(

1. I used the motoG as a data only sim
2. Then added the motoG phone to my account with full Fi service (which was recommended by the last customer)

Please help

[Matt Rubashkin @mrubash1]

Powerful new study by my colleagues at @getusppe , and great reporting by @zoeschlanger !

Thanks for contributing to the survey and data analysis Keyon, Charlotte, Shuhan, Suhas, Alex, Dan and more!

[TIME @TIME]

Begging for thermometers, body bags, and gowns: U.S. health care workers are dangerously ill-equipped to fight COVID-19 https://t.co/vwTkllblGy

[Matt Rubashkin @mrubash1]

10,000 Face Shields for Front Line Health Workers! Amazing grass roots fundraising by Something Labs: https://t.co/cUs3UXluBt

[Reza Zadeh @Reza_Zadeh]

Drifting in an autonomous vehicle. Uses rotation rate of the vehicle’s velocity vector to track the path, while yaw acceleration is used to stabilize sideslip. Could help autonomous vehicles in emergencies. Fun results. https://t.co/ha6iqzIYMR

[Matt Rubashkin @mrubash1]

Cool new tool from @streamlit team!
https://t.co/DUdKmZ1OsQ

[Insight @InsightFellows]

Working with a new Python object can be challenging. Learn how to deeply inspect objects yourself, or use this pip installable CLI tool that’ll do the work for you! #python #MachineLearning #programming
https://t.co/1MzayxQzOU

[Insight @InsightFellows]

Insight is expanding to Los Angeles! Apply now for Data Science & Data Engineering Fellows Programs starting September 2019. https://t.co/ONpUNg3kZO

[Matt Rubashkin @mrubash1]

Discrimination in ML models is a huge issue across many industries. Check out this awesome blog post about how to tackle bias in ML Models! https://t.co/XK3wF0SCc3
@InsightDataAI @AstronomerAmber @EmmanuelAmeisen

[Insight @InsightFellows]

Insight Program Director, and former Fellow, @AstronomerAmber, discusses her recommender system for improved preference predictions. #ArtificialIntelligence #MachineLearning https://t.co/UqxpMg4cTl

[Sherry.Lynn @Sherry_13aby]

@CaltransDist3 any updates on I80?

[Insight @InsightFellows]

. @InsightDataAI Fellow Shaobo Guan (@summitkwan) explains how he built a novel GAN architecture at Insight that allows us to generate custom photo-realistic images of faces based on any attribute.

https://t.co/gH8ppOsgYN

[Matt Rubashkin @mrubash1]

Interested in building an ML Project, check out this great article from @EmmanuelAmeisen from Insight Data and Adam Coates of Khosla!

[Insight @InsightFellows]

Learn concrete tips on how to successfully build useful #MachineLearning projects from @EmmanuelAmeisen, Head of AI @InsightDataSci and @adampaulcoates, operating partner @khoslaventures. https://t.co/XyEjSTkWw0

[Insight @InsightFellows]

Learn how to quickly build your own prototype of @Google Image Search using #DeepLearning to build expressive representations, by following @InsightDataAI lead @EmmanuelAmeisen's step-by-step guide on our blog https://t.co/lyWIDd9C2w