Towards AI
FEBRUARY 10, 2023
Unlocking the Power of Real-time Predictions: An Introduction to Incremental Machine Learning for Linked Data Event Streams Photo by Isaac Smith on Unsplash This article discusses online machine learning, one of the most exciting subdomains of machine learning theory. LDES workbench in Apache NIFI (Image by the author.)
Marktechpost
AUGUST 19, 2023
Modeling the underlying academic data as an RDF knowledge graph (KG) is one efficient method. This makes standardization, visualization, and interlinking with Linked Data resources easier. As a result, scholarly KGs are essential for converting document-centric academic material into linked and automatable knowledge structures.
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AWS Machine Learning Blog
APRIL 7, 2023
As one of the most prominent use cases to date, machine learning (ML) at the edge has allowed enterprises to deploy ML models closer to their end-customers to reduce latency and increase responsiveness of their applications. Even ground and aerial robotics can use ML to unlock safer, more autonomous operations. Instances[*].
Topbots
JUNE 22, 2023
ChatGPT is a GPT ( G enerative P re-trained T ransformer) machine learning (ML) tool that has surprised the world. Moreover, its capacity to be an ML model trained for general tasks and perform very well in domain-specific situations is impressive. which ranked best on the test set) named their ML architecture Fortia-FBK.
Mlearning.ai
MAY 10, 2023
Github : [link] Data Augmentation Techniques Engineers could also explore data augmentation techniques to increase the diversity and complexity of training data for AI algorithms. DALL-E generates images based on textual descriptions, allowing for more control over the content of the generated images.
Marktechpost
JULY 13, 2023
They can provide a logical justification for such phase changes thanks to this link. Data on the flow of cognition throughout training. Based on these findings, they investigate the possible advantages of chain-of-thought data during training. Check out the Paper and Github link.
Unite.AI
AUGUST 15, 2024
Under the academic leadership of Turing Award winner Michael Stonebraker, the question the team were investigating was “can we link data records across hundreds of thousands of sources and millions of records.” Bad data for them could mean a provider gets more shifts than they can handle, leading to burnout.
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