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Category: robotics/AI – Page 1,543

New Lunar Satellites Will Enable Autonomous Space Travel to the Moon for Astronauts

Both the European Space Agency and NASA are planning to test even more sensitive sensors on future moon missions to try and hone in on satellite signals. If they can truly connect with sats back home, we could get closer to achieving autonomous moon travel. But eventually that won’t be enough. To help direct humans on the lunar surface, we’re going to need a fleet of satellites specifically around the moon. NASA calls its project LunaNet, and it’s part of the Gateway space station, which is the culmination of America’s plan to return to the moon. It needs to be designed to play well with ESA technology and, eventually, will be the source of high-speed internet on the moon.

Artemis I launched back in November, rounded the moon just 81 miles above the lunar surface and touched down Earth-side in December. Artemis II, which will carry astronauts around the moon in a similar trajectory, is slated to launch in late 2024, according to Space.com. Artemis III, which will be humanity’s first boots on the moon since 1972, could launch as early as 2025.

How the quantum realm will go beyond computing

Check out all the on-demand sessions from the Intelligent Security Summit here.

Over the last half-decade, quantum computing has attracted tremendous media attention. Why?

After all, we have computers already, which have been around since the 1940s. Is the interest because of the use cases? Better AI? Faster and more accurate pricing for financial services firms and hedge funds? Better medicines once quantum computers get a thousand times bigger?

How deep learning will ignite the metaverse in 2023 and beyond

Check out all the on-demand sessions from the Intelligent Security Summit here.

The metaverse is becoming one of the hottest topics not only in technology but in the social and economic spheres. Tech giants and startups alike are already working on creating services for this new digital reality.

The metaverse is slowly evolving into a mainstream virtual world where you can work, learn, shop, be entertained and interact with others in ways never before possible. Gartner recently listed the metaverse as one of the top strategic technology trends for 2023, and predicts that by 2026, 25% of the population will spend at least one hour a day there for work, shopping, education, social activities and/or entertainment. That means organizations that use the metaverse effectively will be able to engage with both human and machine customers and create new revenue streams and markets.

GPT-4 could pass Bar Exam, AI researchers say

Researchers tested GPT-3.5 with questions from the US Bar Exam. They predict that GPT-4 and comparable models might be able to pass the exam very soon.

In the U.S., almost all jurisdictions require a professional license exam known as the Bar Exam. By passing this exam, lawyers are admitted to the bar of a U.S. state.

In most cases, applicants must complete at least seven years of post-secondary education, including three years at an accredited law school.

Will ChatGPT or Twitter Become the End of Human Intelligence?

Benjamin Franklin stated, “If you would not be forgotten as soon as you are dead and rotten, either write things worth reading, or do things worth the writing.”

MIT’s well-known late Director of Artificial Intelligence Laboratory, Patrick Winston, expanded upon this adage, saying, “Your success in life will be determined largely by your ability to speak, your ability to write, and the quality of your ideas. In that order.”

We are at a precarious point in human development, with the positive and negative impact of technology surrounding us as individuals and as a society. Technology has helped improve our living standards, extended our lives, cured diseases, fed our growing populations, and expanded our frontiers. But it has also helped create greater economic and digital divides, increased pollution and harm to our environment, and potentially endangered the intellectual development of our human population.

Automated interpretable discovery of heterogeneous treatment effectiveness: A COVID-19 case study

Year 2022 😗

Testing multiple treatments for heterogeneous (varying) effectiveness with respect to many underlying risk factors requires many pairwise tests; we would like to instead automatically discover and visualize patient archetypes and predictors of treatment effectiveness using multitask machine learning. In this paper, we present a method to estimate these heterogeneous treatment effects with an interpretable hierarchical framework that uses additive models to visualize expected treatment benefits as a function of patient factors (identifying personalized treatment benefits) and concurrent treatments (identifying combinatorial treatment benefits). This method achieves state-of-the-art predictive power for COVID-19 in-hospital mortality and interpretable identification of heterogeneous treatment benefits. We first validate this method on the large public MIMIC-IV dataset of ICU patients to test recovery of heterogeneous treatment effects. Next we apply this method to a proprietary dataset of over 3,000 patients hospitalized for COVID-19, and find evidence of heterogeneous treatment effectiveness predicted largely by indicators of inflammation and thrombosis risk: patients with few indicators of thrombosis risk benefit most from treatments against inflammation, while patients with few indicators of inflammation risk benefit most from treatments against thrombosis. This approach provides an automated methodology to discover heterogeneous and individualized effectiveness of treatments.

The rise of automation in drug discovery

Year 2022 😗

Automation is not just for high-throughput screening anymore. New devices and greater flexibility are transforming what’s possible throughout drug discovery and development. This article was written by Thomas Albanetti, AstraZeneca; Ryan Bernhardt, Biosero; Andrew Smith, AstraZeneca and Kevin Stewart, AstraZeneca for a 28-page DDW eBook, sponsored by Bio-Rad. Download the full eBook here.

A utomation has been a part of the drug discovery industry for decades. The earliest iterations of these systems were used in large pharmaceutical companies for high-throughput screening (HTS) experiments. HTS enabled the testing of libraries of small molecule compounds by a single or a series of multiple experimental conditions to i dentify the potential of those compounds as a treatment for a target disease. HTS has evolved to enable screening libraries of millions of compounds, but the high cost of equipment has largely resulted in automation occurring primarily in large pharmaceutical companies. Today, though, new types of robots paired with sophisticated software tools have helped to democratise access to automation, making it possible for pharma and biotechnology companies of almost any size to deploy these solutions in their labs.

Originally, automated solutions were only implemented for projects that involved a lot of repetitive tasks, which is typical of high-throughput experiments and assays. The equipment used in early automation efforts was expensive, specialised, and physically integrated together, effectively making the equipment unavailable for any non-automated use. Now, both the approaches and equipment are far more adaptive and flexible. The latest automation software is also much simpler to program, making it easier to swap in different instruments and robots as needed. For example, labs can run a particular HTS assay for a few weeks and then quickly pivot to run a new assay. Labs can also create and run bespoke standard operating procedures, assays, and experiments for drug targets they are interested in pursuing.

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