AI from a Psychologist’s Point of View

Researchers at the Max Planck Institute for Biological Cybernetics in Tübingen have examined the general intelligence of the language model GPT-3, a powerful AI tool. Using psychological tests, they studied competencies such as causal reasoning and deliberation, and compared the results with the abilities of humans. Their findings, in the paper “Using cognitive psychology to understand GPT-3” paint a heterogeneous picture: while GPT-3 can keep up with humans in some areas, it falls behind in others, probably due to a lack of interaction with the real world.

How AI Can be Used to Help People See

From reducing the reliance on trial and error to providing ultra-precise drug effectiveness data, AI has a major role to play in making clinical trials more efficient and robust. In this contributed article, ophthalmologist and biopharma CEO Dr George Magrath explains how AI is being harnessed in the development of eye care medicines.

CATALOG Achieves Historic DNA Computing Milestone

Catalog Technologies, Inc., a leader in DNA-based digital data storage and computation, has made a historic breakthrough in DNA computation by demonstrating the ability to search data stored in DNA in a massively parallel and scalable manner with resource usage almost independent of the data size. 

The Move Toward Green Machine Learning

A new study suggests tactics for machine learning engineers to cut their carbon emissions. Led by David Patterson, researchers at Google and UC Berkeley found that AI developers can shrink a model’s carbon footprint a thousand-fold by streamlining architecture, upgrading hardware, and using efficient data centers. 

NVIDIA Launches Large Language Model Cloud Services

NVIDIA today announced two new large language model cloud AI services — the NVIDIA NeMo Large Language Model Service and the NVIDIA BioNeMo LLM Service — that enable developers to easily adapt LLMs and deploy customized AI applications for content generation, text summarization, chatbots, code development, as well as protein structure and biomolecular property predictions, and more.

Climate Change is an Existential Threat, and Businesses Need Data to Fight It

In this contributed article, Or Lenchner, CEO, Bright Data, examines how public web data collection is essential to ESG efforts in 2022. The recent International Panel on Climate Change report warned that we aren’t doing enough to avoid the dire impacts of climate change – businesses must use every tool at their disposal to support the fight against climate change, especially quality data.

How AI Unlocks The Secrets Behind Sports Rehab and CBD

In this contributed article, Scott Mazza, co-founder and COO of Vitality CBD, discusses groundbreaking discoveries in sports rehab, specifically how big data is the differentiator – ML algorithms and AI-powered tools will be invaluable for trawling through scientific literature to find relevant studies as well as combining different datasets.

New Streamlined Statistical Method Provides Improved Pattern Detection and Risk Prediction for Disease

Researchers from the Renaissance Computing Institute (RENCI) at UNC-Chapel Hill, Perspectrix, the UNC School of Medicine, and the WVU Rockefeller Neuroscience Institute have collaborated to develop a new method for finding patterns in data which arguably surpasses the performance of a generally accepted “gold standard.”

H2O.ai Showcases Healthcare and Life Sciences Leadership with Customer Successes, Breadth of AI Apps

H2O.ai, an AI Cloud leader, announced it has expanded its healthcare capabilities, now offering 40 AI applications across population health, precision medicine, public health and intelligent supply chain, supporting customers throughout the healthcare ecosystem including Bon Secours Mercy Health (BSMH) and Kaiser Permanente.  

Big Data in Life Sciences – Why ‘doing things the old way’ is the Biggest Barrier to Progress

In this special guest feature, Zachary Pitluk, Ph.D., Vice President of Life Sciences and Healthcare at Paradigm4, highlights how real insight comes, not from data collection, but from intelligent data curation, computation, and application. Many are convinced that the life sciences industry inertia needs to change in terms of willingness to take a step back from old school wisdom and consider new methods and new approaches.