Modern bioprocess development is significantly influenced by machine learning (ML), which is a part of a wide range of analytics techniques, digitalisation, and automation methods. These tools generate large sets of experimental data which are crucial in the optimisation of bioprocessing methodologies. With the help of ML, these vast datasets can be efficiently examined to…
Modern bioprocess management, guided by sophisticated analytical techniques, digitalization, and automation, is generating abundant experimental data crucial for process optimization. Machine Learning (ML) techniques have proven crucial in analyzing these huge datasets, allowing for the efficient exploration of design spaces in bioprocessing. ML techniques are utilized in strain engineering, bioprocess optimization, scale-up, and real-time monitoring…
Meta's Fundamental AI Research (FAIR) team has announced several significant advances in the field of artificial intelligence, reinforcing their commitment to collaboration, openness, and responsible artificial intelligence development. With a focus on principles of excellence and scalability, the team's aim is to foster cutting-edge innovation.
Meta FAIR has launched six key research artifacts which include innovative…
Meta's Fundamental AI Research (FAIR) team has made significant advancements and contributions to AI research, models, and datasets recently that align with principles of openness, collaboration, quality, and scalability. Through these, the team aims to encourage innovation and responsible development in AI.
Meta FAIR has made six key research artifacts public, as part of an aim…
Open-source pre-training datasets play a critical role in investigating data engineering and fostering transparent and accessible modeling. Recently, there has been a move from frontier labs towards the creation of large multimodal models (LMMs) requiring sizable datasets composed of both visual and textual data. The rate at which these models advance often exceeds the availability…
In the current economic climate, getting the maximum benefit of their Snowflake investment is crucial for data teams. As a data warehouse, Snowflake facilitates data storage and management in its cloud-based environment. However, cost optimization in Snowflake remains a major concern for data teams, who often spend a considerable amount of time manually looking for…
AI in healthcare isn’t about replacing human doctors but about augmenting their abilities, like the synergy between Luke Skywalker and R2D2 in Star Wars. Rather than extra 'boots on the ground,' AI serves as extra 'circuits on the ground,' helping clinicians navigate obstacles in patient care swiftly and efficiently.
AI has come a long way since…
The emergency department (ED) plays a crucial role in providing immediate healthcare to individuals with a range of conditions. However, overcrowding in EDs can compromise the delivery of prompt and effective assistance, having significant clinical and economic consequences. Many inpatient hospital admissions come via the ED; thus, its effectiveness can significantly impact overall clinical care.
The…
GPUs, or Graphics Processing Units, are powerful processors and essential components for running artificial intelligence (AI) algorithms. However, their high acquisition and maintenance costs often make them inaccessible to small businesses, individual initiatives, and academic institutions. Recognizing an opportunity in the AI revolution, which has driven a high demand for GPUs, GPUDeploy offers a solution…
Reinforcement learning (RL) is often used to train large language models (LLMs) for use as AI assistants. By assigning numerical rewards to outcomes, RL encourages behaviours that result in high-reward outcomes. However, a poorly stated reward signal can lead to 'specification gaming', where the model learns behaviours that are undesirable but highly rewarded.
A range of…