Research Archives - Liwaiwai

A Better Way To Study Ocean Currents

A new machine-learning model makes more accurate predictions about ocean currents, which could help with tracking plastic pollution and oil spills, and aid in search and rescue. Computer scientists at MIT joined forces with oceanographers to develop a machine-learning model that incorporates knowledge from fluid dynamics to generate more accurate predictions about the velocities of ocean currents. This figure shows drifting buoy trajectories in the Gulf of Mexico superimposed on surface currents. The red dots mark the buoys’ positions on March 9, 2016, and the tails are 14 days long. To study ocean currents, scientists release GPS-tagged buoys in the…

Google Cloud Launches AI-Powered Solutions To Safely Accelerate Drug Discovery And Precision Medicine

Cerevel and Pfizer are using the Target and Lead Identification Suite—and Colossal Biosciences is adopting the Multiomics Suite—to bring therapeutics to market faster BOSTON, May 16, 2023 /PRNewswire/ — Today at the Bio-IT World Conference, Google Cloud announced two new AI-powered life sciences solutions to accelerate drug discovery and precision medicine for biotech companies, pharmaceutical firms, and public sector organizations. Available worldwide today, the Target and Lead Identification Suite helps researchers better identify the function of amino acids and predict the structure of proteins; and the Multiomics Suite accelerates the discovery and interpretation of genomic data, helping companies design precision treatments. Cerevel, Colossal…

Humanity VS Intelligence VS Artificial Intelligence, And Areas Of Study

Humanity refers to the collective qualities, characteristics, and behaviors that are associated with being human. It encompasses a wide range of traits and qualities, including: 1. Empathy: The ability to understand and share the feelings of others. 2. Compassion: The ability to show concern and kindness for others. 3. Creativity: The ability to generate new and innovative ideas. 4. Curiosity: The desire to learn and explore. 5. Rationality: The ability to think critically and logically. 6. Collaboration: The ability to work together towards a common goal. 7. Diversity: The recognition and acceptance of differences between individuals and groups. Humanity is…

Robot | AI | Technology

ASML And Eindhoven University Of Technology Strengthen Longstanding Collaboration

Stronger partnership through extended joint research programs and collaborative facilities ANNOUNCEMENT – VELDHOVEN, THE NETHERLANDS, APRIL 24, 2023 ASML today announced a new phase in its longstanding partnership with Eindhoven University of Technology (TU/e), the leading academic institution in Brainport Eindhoven. This includes a jointly defined research program, the construction of a new ASML research facility on the TU/e campus, including the creation of a state-of-the-art cleanroom. The two parties signed a memorandum of understanding to jointly develop a 10-year strategic research road map in the fields of plasma physics, artificial intelligence, mechatronics and semiconductor lithography. The TU/e and ASML will…

Our Progress Toward Quantum Error Correction

Three years ago, our quantum computers were the first to demonstrate a computational task in which they outperformed the fastest supercomputers. It was a significant milestone on our roadmap toward building a large-scale quantum computer, and the “hello world” moment so many of us had been hoping for. Yet in the long arc of scientific progress it was just one step towards making quantum applications meaningful to human progress. Now, we’re taking another big step forward: For the first time ever, our Quantum AI researchers have experimentally demonstrated that it’s possible to reduce errors by increasing the number of qubits. In quantum computing, a qubit is…

Machine Learning

Efficient Technique Improves Machine-Learning Models’ Reliability

The method enables a model to determine its confidence in a prediction, while using no additional data and far fewer computing resources than other methods. Powerful machine-learning models are being used to help people tackle tough problems such as identifying disease in medical images or detecting road obstacles for autonomous vehicles. But machine-learning models can make mistakes, so in high-stakes settings it’s critical that humans know when to trust a model’s predictions. Uncertainty quantification is one tool that improves a model’s reliability; the model produces a score along with the prediction that expresses a confidence level that the prediction is…

How AI Can Worsen Health Care Disparities?

Data sources that “teach” artificial intelligence could amplify and worsen disparities in health care, says law professor Nicholson Price. Those data sources are not representative and/or are based on data from current unequal care, says Price, a member of the University of Michigan’s Institute for Healthcare Policy & Innovation. In a recent article in Science, Price and colleagues Ana Bracic of Michigan State University and Shawneequa Callier of George Washington University say these disparities are happening despite efforts in medicine by physicians and health systems trying strategies focused on diverse workforce recruitment or implicit bias training. Here, Price answers questions about bias and AI in healthcare: Q What is an example of anti-minority culture? A…

Artificial Intelligence’s Promise And Peril

AS ALGORITHMS ANALYZE MAMMOGRAMS AND SMARTPHONES CAPTURE LIVED EXPERIENCES, RESEARCHERS ARE DEBATING THE USE OF AI IN PUBLIC HEALTH. John Quackenbush was frustrated with Google. It was January 2020, and a team led by researchers from Google Health had just published a study in Nature about an artificial intelligence (AI) system they had developed to analyze mammograms for signs of breast cancer. The system didn’t just work, according to the study, it worked exceptionally well. When the team fed it two large sets of images to analyze—one from the UK and one from the U.S.—it reduced false positives by 1.2 and 5.7 percent and…

Mammoth AI Report Says Era Of Deep Learning May Fade, But That’s Unlikely

Scholars see deep learning’s pitfalls and limitations, the computer industry just sees a huge opportunity in matrix multiplications. The era of deep learning began in 2006, when Geoffrey Hinton, a professor at the University of Toronto, who is one of the founders of that particular approach to artificial intelligence, theorized that greatly improved results could be achieved by adding many more artificial neurons to a machine learning program. The “deep” in deep learning refers to the depth of a neural network, how many layers of artificial neurons data is passed through. Hinton’s insight led to breakthroughs in the practical performance of AI…

How Humans And Machines Can Enhance Each Other’s Strengths With Collaborative Intelligence

“Artificial intelligence is transforming all sectors of the economy, but there’s no reason to fear that robots will replace all human employees. In fact, companies that automate their operations mainly to cut their workforces will see only short-term productivity gains, say the authors. Their research, involving 1,500 firms in a range of industries, shows that the biggest performance improvements come when humans and smart machines work together, enhancing each other’s strengths. People need to train AI agents, explain their outputs, and make sure they are used responsibly. AI agents, in turn, can assist people with information gathering, data crunching, routine…

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