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LLM hype brings memories of IBM Watson

Ehud Reiter

IBM then tried to commercialise Watson, under the tag “cognitive computing”; I think it spend billions on this. One project which was mentioned in almost all of the ones I saw was a system which would help doctors treat cancer. The system was very impressive for the time, a striking achievement!

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10 everyday machine learning use cases

IBM Journey to AI blog

AI-enabled computer vision is often used to analyze mammograms and for early lung cancer screening. Doctors evaluating mammograms for breast cancer miss 40% of cancers, and ML can improve on that figure. Then, it suggests the social media user tag that individual.

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The most valuable AI use cases for business

IBM Journey to AI blog

Clarify computer vision AI-powered computer vision enables image segmentation , which has a wide variety of use cases, including aiding diagnosis in medical imaging, automating locomotion for robotics and self-driving cars, identifying objects of interest in satellite images and photo tagging in social media.

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NLP Summit Insights: How LLMs Are Shaping the Future of Modern Business

John Snow Labs

Supriya Raman, VP of Data Science at JPMorgan, comments, “Using LLMs on domain-specific knowledge bases ensures that we can fine-tune them on data specific to our organization or domain, improving search accuracy, automating tagging, and even generating new content.

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Efficiently fine-tune the ESM-2 protein language model with Amazon SageMaker

AWS Machine Learning Blog

Various cancers Data source: Urquhart, L. Name Manufacturer 2022 Global Sales ($ billions USD) Indications Comirnaty Pfizer/BioNTech $40.8 COVID-19 Spikevax Moderna $21.8 COVID-19 Humira AbbVie $21.6 Arthritis, Crohn’s disease, and others Keytruda Merck $21.0 Top companies and drugs by sales in 2022.

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Scale AI training and inference for drug discovery through Amazon EKS and Karpenter

AWS Machine Learning Blog

Iambic Therapeutics is a drug discovery startup with a mission to create innovative AI-driven technologies to bring better medicines to cancer patients, faster. v1alpha5 kind: ClusterConfig metadata: name: do-eks-yaml-karpenter version: '1.28' region: us-west-2 tags: karpenter.sh/discovery:

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Meet ConDistFL: A Revolutionary Federated Learning Approach for Organ and Disease Segmentation in CT Datasets

Marktechpost

It is also difficult to annotate the organs and associated cancers of diverse anatomies and imaging modalities since even professionals sometimes only have specialized expertise for a single activity. Unfortunately, a lack of training data resulted from the expensive expense of high-quality medical imaging data.