Bioprocesses are central to modern biotechnology, enabling sustainable production in pharmaceuticals, specialty chemicals, cosmetics, and food. However, developing high-performing processes is costly and complex, requiring iterative, multi-scale experimentation from microtiter plates to pilot reactors. Conventional Design of Experiments (DoE) approaches often struggle to address process scale-up and the joint optimization of reaction conditions and biocatalyst selection. We propose a multi-fidelity batch Bayesian optimization framework to accelerate bioprocess development and reduce experimental costs. The method integrates Gaussian Processes tailored for multi-fidelity modeling and mixed-variable optimization, guiding experiment selection across scales and biocatalysts. A custom simulation of a Chinese Hamster Ovary bioprocess, capturing non-linear and coupled scale-up dynamics, is used for benchmarking against multiple simulated industrial DoE baselines. Multiple case studies show how the proposed workflow can achieve a reduction in experimental costs and increased yield. This work provides a data-efficient strategy for bioprocess optimization and highlights future opportunities in transfer learning and uncertainty-aware design for sustainable biotechnology.

Bayesian optimization (BO) is an attractive machine learning framework for performing sample-efficient global optimization of black-box functions. The optimization process is guided by an acquisition function that selects points to acquire in each round of BO. In batched BO, when multiple points are acquired in parallel, commonly used acquisition functions are often high-dimensional and intractable, leading to the use of sampling-based alternatives. We propose a statistical physics inspired acquisition function for BO with Gaussian processes that can natively handle batches. Batched Energy-Entropy acquisition for BO (BEEBO) enables tight control of the explore-exploit trade-off of the optimization process and generalizes to heteroskedastic black-box problems. We demonstrate the applicability of BEEBO on a range of problems, showing competitive performance to existing methods.

The suspect in Charlie Kirk's assassination has been captured, FBI director Kash Patel announced MSNBC sparks outrage for'disgusting' Charlie Kirk comments following Utah shooting Tragedy as Charlie Kirk's wife left behind with two young children after conservative activist is fatally shot A DEI mayor, an inconvenient crime and video they never wanted you to see: MAUREEN CALLAHAN knows why the Left has sympathy for that killer... but none for his victim Sweater weather starts here - the cozy, chic pieces from Soft Surroundings you'll actually wear all season We only had one symptom we dismissed... but then we were diagnosed with the rarest form of melanoma Soft-touch prosecutor let felon walk free... before crook'slit Auburn professor's throat in random attack' I tried the 30 cent'miracle chill pill' before a big event.. now I'm taking it for everything Donald Trump and House Republicans lead prayers for Charlie Kirk's family after conservative star is fatally shot Prince Harry says his father King Charles is'great' following their first meeting in 19 months... which was over a cup of tea and just 55 minutes long Liberal media defends thug who killed Ukrainian woman in cold blood: 'This man was hurting' Knifeman accused of stabbing Ukrainian refugee to death gives chilling reason for the attack... as he speaks for the first time from jail on the murder that shocked America Fox News reveals new lineup and elevates star White House reporter who's sparred with Trump Horrific new details of passenger injuries after they were'thrown' around Delta flight during'severe turbulence' Hilarious video reveals how apes dance just like humans - with moves'like a cross between the robot and vogueing' Like a cross between Peter Crouch and Michael Jackson, a hilarious video reveals the moment a cheeky gibbon performs a dance for a captive audience. The female, filmed at a rescue centre in Ninh Bình, Vietnam, has her back turned as she dramatically drops and shifts, described as a'cross between a robot dance and vogueing'. Scientists have observed seven gibbons performing the elaborate dance, consisting of jerky sideways and upward movements worthy of a 1970s New York nightclub. Not only is the dance human-like, but the gibbons perform it for humans - possibly to get attention when they're hungry. Already, primates other than humans are known to dance - some even while listening to music - but few are quite as remarkably stylized as this.

Male and female lar gibbons sing duets with notes that are synchronised and occur at regular intervals. These are rhythmic qualities similar to those found in human songs, which could hint at an evolutionary basis for the origins of music. "I'm pretty sure the gibbon's isochronous capacities are better than mine," says Andrea Ravignani at the Max Planck Institute for Psycholinguistics in the Netherlands, referring to the capacity to sing notes that occur at regularly repeating intervals. This ability has previously been noted in indris (Indri indri), a type of lemur found in Madagascar and the only other primate whose calls exhibit distinct rhythms related to those found in human music. Male and female gibbons regularly sing duets to define territory and form social bonds.

With the advent of new techniques, robust systems that can understand the relationships not only between words but words and photos, videos, and audio became possible. At the same time, policymakers -- growing increasingly wary of AI's potential harm -- proposed rules aimed at mitigating the worst of AI's effects, including discrimination. Meanwhile, AI research labs -- while signaling their adherence to "responsible AI" -- rushed to commercialize their work, either under pressure from corporate parents or investors. But in a bright spot, organizations ranging from the U.S. National Institutes of Standards and Technology (NIST) to the United Nations released guidelines laying the groundwork for more explainable AI, emphasizing the need to move away from "black-box" systems in favor of those whose reasoning is transparent. As for what 2022 might hold, the renewed focus on data engineering -- designing the datasets used to train, test, and benchmark AI systems -- that emerged in 2021 seems poised to remain strong.

When one thinks of assembly-line production, a mind likely turns to thoughts of automobile manufacturing and other heavy industrial processes, rather than jumping to artificial intelligence (AI) and apps. But according to recent Wall Street Journal reports, the Mayo Clinic is the most recent organization to use an assembly-line approach to AI development. It is not, of course, an assembly line as it has historically been known. These days, the line workers are small teams working with a common set of software tools and procedures, with an eye toward building out AI applications faster and cheaper by creating a "more consistent process to produce algorithms," according to James Buntrock, vice-chair of the department of information technology at Mayo Clinic. Mayo launched its AI factory last fall and is now gearing up to move into full production, with plans for 60 projects underway.

This paper describes a general-purpose extension of max-value entropy search, a popular approach for Bayesian Optimisation (BO). A novel approximation is proposed for the information gain -- an information-theoretic quantity central to solving a range of BO problems, including noisy, multi-fidelity and batch optimisations across both continuous and highly-structured discrete spaces. Previously, these problems have been tackled separately within information-theoretic BO, each requiring a different sophisticated approximation scheme, except for batch BO, for which no computationally-lightweight information-theoretic approach has previously been proposed. GIBBON (General-purpose Information-Based Bayesian OptimisatioN) provides a single principled framework suitable for all the above, out-performing existing approaches whilst incurring substantially lower computational overheads. In addition, GIBBON does not require the problem's search space to be Euclidean and so is the first high-performance yet computationally light-weight acquisition function that supports batch BO over general highly structured input spaces like molecular search and gene design. Moreover, our principled derivation of GIBBON yields a natural interpretation of a popular batch BO heuristic based on determinantal point processes.

Beyond a Steel Sky, the sequel to classic 1994 point-and-click adventure game Beneath a Steel Sky, hits Apple Arcade on Friday, with a Steam release slated for July. Developer Revolution Software shared a launch trailer that shows what new and returning players can expect from the sequel. Beyond a Steel Sky once again sees players assume the role of series protagonist Robert Foster. After what seems like a lengthy absence, Foster has returned to Union City, the dystopian metropolis where the original game took place. While the city has changed, he still manages to find some of the characters that made his first visit so colorful, including Joey, the sentient robot that helped solve puzzles in the original.