Jay van Zyl @ ecosystem.Ai

Jay van Zyl @ ecosystem.Ai

Analysis and validation of hub genes for atherosclerosis and AIDS and immune infiltration characteristics based on bioinformatics and machine learning – Nature

Analysis and validation of hub genes for atherosclerosis and AIDS and immune infiltration characteristics based on bioinformatics and machine learning  Nature

RelCon: Relative Contrastive Learning for a Motion Foundation Model for Wearable Data – Apple Machine Learning Research

RelCon: Relative Contrastive Learning for a Motion Foundation Model for Wearable Data  Apple Machine Learning Research

Do LLMs Know Internally When They Follow Instructions? – Apple Machine Learning Research

Do LLMs Know Internally When They Follow Instructions?  Apple Machine Learning Research

Artificial Intelligence in Cybersecurity Market is Booming Worldwide | Major Giants- IBM, Cisco, McAfee – openPR.com

Artificial Intelligence in Cybersecurity Market is Booming Worldwide | Major Giants- IBM, Cisco, McAfee  openPR.com

Sorensen Roofing & Restoration Leverages Artificial Intelligence for Streamlined Storm Damage Claims and Repairs – openPR.com

Sorensen Roofing & Restoration Leverages Artificial Intelligence for Streamlined Storm Damage Claims and Repairs  openPR.com

Artificial Intelligence Grows In New Jersey – Business Facilities Magazine

Artificial Intelligence Grows In New Jersey  Business Facilities Magazine

IEA: Electricity Demand From AI Data Centers Set to Surge – energyintel.com

IEA: Electricity Demand From AI Data Centers Set to Surge  energyintel.com

Artificial Intelligence in Education: A Future Revolution Technology – Daily Sundial

Artificial Intelligence in Education: A Future Revolution Technology  Daily Sundial

Data Centers Will Use Twice as Much Energy by 2030—Driven by AI – Scientific American

Data Centers Will Use Twice as Much Energy by 2030—Driven by AI  Scientific American

Incorporation of visible/near-infrared spectroscopy and machine learning models for indirect assessment of grape ripening indicators – Nature

Incorporation of visible/near-infrared spectroscopy and machine learning models for indirect assessment of grape ripening indicators  Nature