2011 Algorithm Database 
MAY 2, 2023
Netflix machine-learning algorithms, for example, leverage rich user data not just to recommend movies, but to decide which new films to make. A blockchain is in essence a large database, decentralized among many users. Generative AI algorithms, like those used to create ChatGPT, train on large language datasets.
Dataconomy
MAY 8, 2024
its Sonio Detect product, which employs advanced deep learning algorithms to enhance ultrasound image quality in real-time, has gained FDA 510(k) approval. Samsung Electronics, which purchased Medison in 2011 for $22 million, holds a 68.45% ownership in the medical device division. In the U.S.,
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Dataconomy
SEPTEMBER 17, 2024
The DSP accepts a request to display an ad, and checks the user profile information in the database, as well as in the database purchased from the DMP. Of course, the big data analysis algorithms of traffic networks will be more modest than those of Facebook, so it is too early to dream of powerful optimization.
Data Science Blog
JUNE 27, 2023
Lambda – Architecture Introduced in 2011 during the peak of Big Data’s prominence, the Lambda architecture remains a significant presence in the field. For existing event sources, listeners are utilized to stream writes directly from database logs or similar data stores.
Hacker News
MARCH 25, 2022
By finding patterns between elements mathematically, transformers eliminate that need, making available the trillions of images and petabytes of text data on the web and in corporate databases. Attention Net didn’t sound very exciting,” said Vaswani, who started working with neural nets in 2011.Jakob Reading Molecules, Medical Records.
IBM Data Science in Practice
JULY 5, 2023
We applied Otter-Knowledge to Drug Discovery, and demonstrated that knowledge-enhanced learned representation enriches protein sequence and SMILES drug databases with a large multi-modal Knowledge Graph fused from different sources. Bindingdb: a web-accessible database of experimentally determined protein–ligand binding affinities.
AWS Machine Learning Blog
MAY 2, 2023
There are a few limitations of using off-the-shelf pre-trained LLMs: They’re usually trained offline, making the model agnostic to the latest information (for example, a chatbot trained from 2011–2018 has no information about COVID-19). They’re mostly trained on general domain corpora, making them less effective on domain-specific tasks.
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