Alexy Khrabrov
Community builder · FunctionalTV
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Community builder · FunctionalTV
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A database system that can synchronize all or a part of its contents over a limited bandwidth link is described. The lowest layer of the system, the bedrock layer, implements a transactional block store. On top of this is a B+-tree that can efficiently compute a digest (hash) of the records within any range of key values in O(log n) time. The top level is a communication protocol that directs the synchronization process such that minimization of bits communicated, rounds of communication, and local computation are simultaneously addressed.
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With the growing availability of data within various scientific domains, generative models hold enormous potential to accelerate scientific discovery. They harness powerful representations learned from datasets to speed up the formulation of novel hypotheses with the potential to impact material discovery broadly. We present the Generative Toolkit for Scientific Discovery (GT4SD). This extensible open-source library enables scientists, developers, and researchers to train and use state-of-the-art generative models to accelerate scientific discovery focused on organic material design.
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ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Gabor Melli Sony Interactive Entertainment Senior Director of Engineering (ML&AI) twitter.com/melli
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Briac Marcatté Twitter Staff ML Engineer https://twitter.com/briacm
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Win's talk here: https://youtu.be/yuT-TTOQta4 Win Wang Twitter Software Engineer Websitehttps://twitter.com/winium
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Michael's talk here: https://youtu.be/Vah1IJDEBao Michael Paul Armbrust Databricks Tech Lead for Delta Lake Berkeley, CA Websitetwitter.com/michaelarmbrust Michael Armbrust is a committer and PMC member of Apache Spark and the original creator of Spark SQL. He currently leads the team at Databricks that designed and built Structured Streaming and the Delta Lake open source project. He received his PhD from UC Berkeley in 2013, and was advised by Michael Franklin, David Patterson, and Armando Fox. His thesis focused on building systems that allow developers to rapidly build scalable interactive applications, and specifically defined the notion of scale independence. His interests broadly include distributed systems, large-scale structured storage and query optimization.
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Tikhon's talk here: https://youtu.be/ePgWU3KZvfQ Tikhon Jelvis Target Principal AI Scientist Berkeley Websitejelv.is I picked up Haskell as my first functional language on a whim, and it's stuck with me ever since. I've worked with other functional languages too—a compiler in Racket, a backend service in OCaml—but now I'm back in the Haskell world, working on Target's supply chain optimization team. Apart from programming in Haskell and giving talks, I also actively write about Haskell and programming on Quora and help organize local meetups and events like BayHac
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Themba's talk here: https://youtu.be/aFfuzIGOWhc Themba Fletcher Crunchbase Themba Fletcher is an enthusiastic technologist, a bit of a polyglot, and an obsessive troubleshooter who loves making things. He currently manages the Core Platform and Data Insights teams at Crunchbase. Fletcher focuses on scaling platforms, APIs, and engineering teams.
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Niole Nelson Domino Data Lab Software Engineer [contact redacted]
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Rob's talk here: https://youtu.be/Gd7yEBguDNA Rob Munro Silicon Valley Humanitarian and Technology experience includes: working in post-conflict development in Liberia and Sierra Leone for UNHCR; researching health communications in Malawi; software development supporting endangered languages; running crowdsourced translation following disasters in Haiti, Pakistan and MENA; hosting aerial image analysis for FEMA following Hurricane Sandy; completing a Stanford PhD focused on AI for low resource languages; tracking epidemics globally; founding Silicon Valley companies focused on technology for all languages for F100s and UNICEF; running product for NLP and Machine Translation at AWS.
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Shoumik's talk here: https://youtu.be/6jJUA_JSCyo Shoumik Palkar Stanford University Ph.D. Student https://twitter.com/sppalkia
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Ryan's talk here: https://youtu.be/ljZP-bvD5Ts Ryan Knight Grand Cloud Principal Software Architect / CEO twitter.com/knight_cloud Ryan Knight is Principal Solution Architect at Grand Cloud. He is a passionate technologist with extensive experience in large scale distributed systems and data pipelines. He first started Java Consulting at the Sun Java Center and has since worked at a wide variety of companies such as Capital One, Starbucks, DataStax, LightBend, Oracle, IBM, Deloitte, and Riot Games. Ryan regularly speaks at conferences in the US and Abroad. In his spare time he enjoys exploring the mountains of Utah with his family.
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Michael Entin Google Inc Software Engineer Seattle, WA Websitemedium.com/@mentin Senior Software Engineer at Google BigQuery team. Before joining Dremel team, worked on various data processing projects at Microsoft: SQL Server Integration Services, Analysis Services, distributed platform for AdCenter Business Intelligence, etc.
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference For more content like this: SBTB-23 is back in person! bay.news/tickets Nov 13-15, Oakland. LLM workshop; AI, Data & Cloud software engineering.
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Joe's talk here: https://youtu.be/HN1c8-93hLs Joe Beda VMware Principal Engineer Seattle, WA Doing cloud native stuff at VMware
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out the talk here: https://youtu.be/U0X0kxLkuA4 Chris Fregly PipelineAI Founder San Francisco, CA twitter.com/cfregly Chris Fregly is Founder and Research Engineer at PipelineIO, a Streaming Machine Learning and Artificial Intelligence Startup based in San Francisco. He is also an Apache Spark Contributor, a Netflix Open Source Committer, founder of the Global Advanced Spark and TensorFlow Meetup, author of the O’Reilly Training and Video Series titled, "High Performance TensorFlow in Production." Previously, Chris was a Distributed Systems Engineer at Netflix, a Data Solutions Engineer at Databricks, and a Founding Member and Principal Engineer at the IBM Spark Technology Center in San Francisco.
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Rashmi's talk here: https://youtu.be/qyzVWq1aSUg Rashmi Shamprasad Netflix Senior Data Engineer Passionate about all things data, Rashmi Shamprasad is a Senior Data Engineer on the Growth Data Engineering team at Netflix, building data products that enable Non Member Acquisition & Experimentation. With over 9 years of experience working in Big Data, her previous stints include building Big Data solutions at PayPal and eBay. Rashmi holds a Masters in Computer Applications and Bachelors in Commerce.
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Russel's talk here: https://youtu.be/jI1Fk9JDm_4 Russell Spitzer DataStax Software Engineer Greater New Orleans Area twitter.com/RussSpitzer Spark, Cassandra, or Dogs.
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out the talk here: https://youtu.be/6RXES-ICTSE Justin Kaeser JetBrains Software Developer twitter.com/ebenwert
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Oscar's talk here: https://youtu.be/HyYpMJNVoVk Oscar Boykin Stripe Machine Learning Infrastructure Maui, HI, US twitter.com/posco Oscar is the creating of Scalding, Summingbird, and Algebird, and is an overall professor and mathematician turned software magician.
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Paul's talk here: https://youtu.be/PJ7ozyLnaEY Paul Cleary Comcast Senior Principal Engineer Philadelphia, PA twitter.com/pauljamescleary 20+ years of software development experience, spent most of the last 5 years in Scala. Most of my career is building OO systems, recently converted to FP. After all this time I am still learning. Talk to me if you are struggling with Scala or Functional Programming or if you are interested in network function programming in Rust.
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Oli's talks here: https://youtu.be/QEjhS2xuunE https://youtu.be/tP77Ryy9Qxs Oli Makhasoeva 47 Degrees Solutions Architect Bellevue, Washington twitter.com/Oli_kitty
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Kaoru's talk here: https://youtu.be/LprhvXhVh1E
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Tabitha's talk here: https://youtu.be/LprhvXhVh1E
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Jason's talk here: https://youtu.be/UpkOZQdROUs Jason Swartz Twitch Software Developer Oakland, CA dtwitter.com/swartzrock Building the next generation of scalable edge services at Twitch. Author of Learning Scala (O'Reilly Media, 2014)
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Check out Nick's talk here: https://youtu.be/f9aJ4cnio1M Nick Pentreath IBM Principal Engineer - Center for Open Source Data & AI Technologies (CODAIT) Websitedeveloper.ibm.com Nick Pentreath is a principal engineer in IBM's Center for Open-source Data & AI Technology (CODAIT), where he works on machine learning. Previously, he cofounded Graphflow, a machine learning startup focused on recommendations. He has also worked at Goldman Sachs, Cognitive Match, and Mxit. He is a committer and PMC member of the Apache Spark project and author of Machine Learning with Spark. Nick is passionate about combining commercial focus with machine learning and cutting-edge technology to build intelligent systems that learn from data to add business value.
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