Lifeboat Foundation

Researchers from the University of Geneva (UNIGE), the Geneva University Hospitals (HUG), and the National University of Singapore (NUS) have developed a novel method for evaluating the interpretability of artificial intelligence (AI) technologies, opening the door to greater transparency and trust in AI-driven diagnostic and predictive tools. The innovative approach sheds light on the opaque workings of so-called “black box” AI algorithms, helping users understand what influences the results produced by AI and whether the results can be trusted.

This is especially important in situations that have significant impacts on the health and lives of people, such as using AI in medical applications. The research carries particular relevance in the context of the forthcoming European Union Artificial Intelligence Act which aims to regulate the development and use of AI within the EU. The findings have recently been published in the journal Nature Machine Intelligence.

Time series data—representing the evolution of information over time—is everywhere: for example in medicine, when recording heart activity with an electrocardiogram (ECG); in the study of earthquakes; tracking weather patterns; or in economics to monitor financial markets. This data can be modeled by AI technologies to build diagnostic or predictive tools.

During a tense opening weekend at SXSW, following the sudden collapse of Silicon Valley Bank which banked nearly half of US venture-backed startups, billionaire investor Mark Cuban sat down with me to discuss options for entrepreneurs trying to secure funds in the midst of unprecedented economic chaos.

“I would encourage people to do their homework,” he said. “This is a learning experience. It’s been a learning experience for me.”

With credit tightening and banks failing, many startups are having a hard time accessing the private equity markets. But fortunately, capital is available from a variety of sources without having to give up equity. Interviews with Mark Cuban and others highlight funds awarding big bucks.

Continue reading “Mark Cuban, SBA And Google On How AI Startups Can Get $2 Million In Funding Amid The Bank Crisis” »

Data analytics teams around the world are failing to bring value to their organisations. According to a survey by market research firm Gartner published on Wednesday, most data and analytics leaders reported that their teams do not provide effective value to the organisation. This is despite increased interest from the industry in investing in data and analytics to improve efficiency in business.

The research report noted that while the lack of available talent is the top impediment for which data and analytics teams are failing to add value to their firms, as reported by 39% of executives, other roadblocks, such as lack of resources and funding to support the programmes and lack of support from top management are also hindering data and analytics projects. Besides, culture challenges to accept change and overall poor data literacy in organisations are among other reasons why many of these projects continue to suffer.

At a time when technology companies are already facing the brunt of layoffs in the face of uncertain economic conditions, teams not performing well or failing to add value to the organisation can face dire consequences, believe experts.

US gaming and computer graphics giant Nvidia has joined forces with an Israeli startup to roll out a new hardware system to connect the quantum computer with classical computers.

The new system, Nvidia DGX Quantum, built together with Israel’s Quantum Machines, a developer of a standard universal language for quantum computers, is expected to be first deployed at Israel’s quantum computing research center at the end of this year.

The quantum computing R&D center funded by the Israel Innovation Authority at an investment of NIS 100 million ($27 million), which is headed by Quantum Machines, was established to help Israel build a quantum computer and advance research in the field that would lead to future developments in economics, technology, security, engineering, and science.

Built Robotics has introduced an autonomous pile driving robot that will help build utility-scale solar farms in a faster, safer, more cost-effective way, and make solar viable in even the most remote locations. Called the RPD 35, or Robotic Pile Driver 35, the robot can survey the site, determine the distribution of piles, drive piles, and inspect them at a rate of up to 300 piles per day with a two-person crew. Traditional methods today typically can complete around 100 piles per day using manual labor.

The RPD 35 was unveiled today at CONEXPO-CON/AGG in Las Vegas, the largest construction trade show in North America and held every three years.

The 2022 Inflation Reduction Act “Building a Clean Energy Economy” section includes a goal to install 950 million solar panels by 2030. With solar farms requiring tens of thousands of 12-to 16-foot-long piles installed eight feet deep with less than an inch tolerance, piles are a critical component of meeting that target.

Year 2022 Basically this mechanoluminescence material can bring illumination to the mysterious info of stress in infrastructure so there could eventually be an easier way to measure aging infrastructure.

Both in Japan and other developed countries, social infrastructure built during periods of rapid economic growth is rapidly aging, and accidents involving aging infrastructure are becoming more frequent. The useful life of infrastructure is considered to be about 50 years due to the deterioration of concrete, a key component. Concrete eventually cracks due to internal chemical reactions and external forces, and so-called “moving cracks” that are gradually progressing due to the constant application of force are particularly dangerous. However, finding such cracks is a difficult task that requires significant time and effort. That’s why Nao Terasaki, a team leader at the National Institute of Advanced Industrial Science and Technology (AIST), and his colleagues have developed a luminescent material that helps reveal dangerous cracks by making them glow.

8 years of cost reduction in 5 weeks: how Stanford’s Alpaca model changes everything, including the economics of OpenAI and GPT 4. The breakthrough, using self-instruct, has big implications for Apple’s secret large language model, Baidu’s ErnieBot, Amazon’s attempts and even governmental efforts, like the newly announced BritGPT.

I will go through how Stanford put the model together, why it costs so little, and demonstrate in action versus Chatgpt and GPT 4. And what are the implications of short-circuiting human annotation like this? With analysis of a tweet by Eliezer Yudkowsky, I delve into the workings of the model and the questions it rises.

Continue reading “The Model That Changes Everything: Alpaca Breakthrough (ft. Apple’s LLM, BritGPT, Ernie and AlexaTM)” »

A new University of Illinois project is using advanced object recognition technology to keep toxin-contaminated wheat kernels out of the food supply and to help researchers make wheat more resistant to fusarium head blight, or scab disease, the crop’s top nemesis.

“Fusarium head blight causes a lot of economic losses in wheat, and the associated toxin, deoxynivalenol (DON), can cause issues for human and animal health. The disease has been a big deterrent for people growing wheat in the Eastern U.S. because they could grow a perfectly nice crop, and then take it to the elevator only to have it get docked or rejected. That’s been painful for people. So it’s a big priority to try to increase resistance and reduce DON risk as much as possible,” says Jessica Rutkoski, assistant professor in the Department of Crop Sciences, part of the College of Agricultural, Consumer and Environmental Sciences (ACES) at Illinois. Rutkoski is a co-author on the new paper in the Plant Phenome Journal.

Increasing resistance to any crop disease traditionally means growing a lot of genotypes of the crop, infecting them with the disease, and looking for symptoms. The process, known in plant breeding as phenotyping, is successful when it identifies resistant genotypes that don’t develop symptoms, or less severe symptoms. When that happens, researchers try to identify the genes related to disease resistance and then put those genes in high-performing hybrids of the crop.

NPL, in collaboration with London Biofoundry and BiologIC Technologies Ltd, have released an analysis on existing and emerging DNA Synthesis technologies in Nature Reviews Chemistry, featuring the work on the front cover.

The study, which was initiated by DSTL, set out to understand the development trajectory of DNA Synthesis as a major industry drive for the UK economy over the next 10 years. The demand for synthetic DNA is growing exponentially. However, our ability to make, or write, DNA lags behind our ability to sequence, or read, it. The study reviewed existing and emerging DNA synthesis technologies developed to close this gene writing gap.

DNA or genes provide a universal tool to engineer and manipulate living systems. Recent progress in DNA synthesis has brought up limitless possibilities in a variety of industry sectors. Engineering biology, therapy and diagnostics, data storage, defense and nanotechnology are all set for unprecedented breakthroughs if DNA can be provided at scale and low cost.