Lifeboat Foundation

Black box optimization methods are used in every domain, from Artificial Intelligence and Machine Learning to engineering and finance. These methods are used to optimize functions when an algebraic model is absent. Black box optimization looks into the design and analysis of algorithms for those problem statements where the structure of the objective function or the limitations defining the set is not known or explainable. Given a set of input parameters, black box optimization methods are designed to evaluate the optimal value of a function. This is done by iteratively assessing the function at multiple points in the input space so as to find the point that generates the optimal output.

Though gradient descent is the most used optimization approach for deep learning models, it is unsuitable for every problem. In cases where gradients cannot be calculated directly or where an objective function’s accurate analytical form is unknown, other approaches like Evolution Strategies (ES) are used. Evolution strategies come from evolutionary algorithms, which refer to a division of population-based optimization algorithms inspired by natural selection. Basically, Evolution Strategies (ES) is a type of Black Box Optimization method that operates by refining a sampling distribution based on the fitness of candidates and updating rules based on equations.

In a new AI paper, researchers from Deepmind, have introduced and developed a new way to use machine learning to learn the update rules from data, called meta-black-box optimization (MetaBBO), to make ES more flexible, adaptable, and scalable. MetaBBO works by meta-learning a neural network parametrization of a BBO update rule. The researchers have used MetaBBO to discover a new type of ES called learned evolution strategy (LES). The learned evolution strategy LES is a type of Set Transformer that updates its solutions based on the fitness of candidates and not depending upon the ordering of candidate solutions within the Black box evaluations. After meta-training, the LES can learn to choose the best-performing solution or update solutions based on a moving average.

Generative artificial intelligence (AI) systems will inspire an explosion of creativity in the music industry and beyond, according to the University of Surrey researchers who are inviting the public to test out their new text-to-audio model.

AudioLDM is a new AI-based system from Surrey that allows users to submit a text prompt, which is then used to generate a corresponding audio clip. The system can process prompts and deliver clips using less computational power than current AI systems without compromising sound quality or the users’ ability to manipulate clips.

The general public is able to try out AudioLDM by visiting its Hugging Face space. Their code is also open-sourced on GitHub with 1000+ stars.

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Scientists shared the latest results from the DART mission this week, six months after its impact into the asteroid Dimorphos.

In 2022, the physics Nobel prize was awarded for experimental work showing that the quantum world must break some of our fundamental intuitions about how the Universe works.

Many look at those experiments and conclude that they challenge “locality” – the intuition that distant objects need a physical mediator to interact. And indeed, a mysterious connection between distant particles would be one way to explain these experimental results.

Others instead think the experiments challenge “realism” – the intuition that there’s an objective state of affairs underlying our experience. After all, the experiments are only difficult to explain if our measurements are thought to correspond to something real.

An international team of planetary scientists has characterized some of the features of an exoplanet named HD-207496-b, located approximately 138 light years from Earth. In their paper accepted for publication in the journal Astronomy & Astrophysics, and currently posted on the arXiv preprint server, the group describes their study of the exoplanet and the two theories regarding its likely makeup.

The exoplanet HD-207496-b was discovered as part of a larger effort to characterize naked core planets. As such, the team was analyzing HARPS spectroscopic observations of HD-207496—a bright k dwarf. By adding TESS photometry data, the group was able to measure the stars’ brightness and wavelength, and by studying the exoplanet’s transit characteristics, the team was able to calculate its period, mass, radius and density. That led them to a bit of a conundrum—was the exoplanet gaseous or watery?

The researchers calculated that the exoplanet had a radius 2.25 times that of Earth, with an orbit of 6.44 days. And it had a mass that was approximately 6.1 times Earth’s. Simple math showed that the exoplanet had a density of 3.27 grams per cubic centimeter, which is less than that of Earth.

Dr. Emily Rice, an Associate Professor of Astrophysics at the Macaulay Honors College of CUNY and resident research associate in the Department of Astrophysics at the American Museum of Natural History (AMNH), is one of the keynote speakers at the TEDxCUNY conference to be hosted on March 10, 2023.

Dr. Rice is extremely involved in the scientific community through her role as a researcher and professor. Dr. Rice co-founded the research group Brown Dwarfs in New York City (BDNYC) with Dr. Kelle Cruz from CUNY Hunter College and Dr. Jackie Faherty from AMNH. Brown Dwarfs are objects that have masses between giant exoplanets and low mass stars. Dr. Rice explained there was a lot about Brown Dwarfs that scientists were yet to explore and understand.

“The three of us started this research group following a small project we had collaborated on,” Dr. Rice said. In 2010, Dr. Cruz had started their work with Hunter College, Dr. Rice was wrapping up her postdoctoral work, and Dr. Faherty was finishing up graduate school. “We all happened to be in New York City at the time, and we were all working with Brown Dwarfs, so we decided to create a research group focused on these substellar objects,” Dr. Rice remarked.

A high-resolution camera mounted on NASA’s Mars Reconnaissance Orbiter has snapped pictures of unusual, almost perfectly circular sand dunes on the Red Planet’s surface.

AI or bust. Right now, AI is what everyone is talking about, and for good reason. After years of seeing AI doled out to help automate the processes that make businesses run smarter, we’re finally seeing AI that can help the average business employee working in the real world. Generative AI, or the process of using algorithms to produce data often in the form of images or text, has exploded in the last few months. What started with OpenAI’s ChatGPT has bloomed into a rapidly evolving subcategory of technology. And companies from Microsoft to Google to Salesforce and Adobe are hopping on board.

What started with ChatGPT has bloomed into an entire subcategory of technology with Meta, AWS, Salesforce, Google, Microsoft all racing to out innovate and deliver exciting generative AI capabilities to consumers, enterprise, developers, and more. Exploring the rapid progress in the AI space.