“The article's source is ArXiv, suggesting that it's a pre-print of a scientific research paper.”

“”

“Zain argues that the current industry standard of running all AI workloads on high-end GPUs is unsustainable for agents, which consume significantly more tokens than traditional LLM applications.”

“This article discusses a Python toolbox, PiML, indicating its focus is likely on code and potentially research around interpretable machine learning.”

“Large language model (LLM) advancements have led to a new paradigm that unifies various natural language processing (NLP) tasks within an instruction-following framework.”

“Lastly, don’t miss Tom’s predictions on what he foresees happening this year as well as his words of encouragement for those new to the field.”

“Cody shares his expertise in the area of data-centric AI, and we dig into techniques like active learning and core set selection, and how they can drive greater efficiency throughout the machine learning lifecycle.”

“We explore the concept of universality between neural representations and deep neural networks, and how these principles of efficiency provide an ability to find consistent features across networks and tasks.”

“The article doesn't contain a direct quote.”

“At TWIMLcon: AI Platforms 2022, our panelists debated the merits of these approaches in The Great MLOps Debate: End-to-End ML Platforms vs Specialized Tools.”

“How should you be thinking about MLOps and the ML lifecycle in that case?”

“Register now at https://twimlcon.com/attend for FREE!”

“The article doesn't contain a direct quote, but rather summarizes the topics discussed.”

“In our conversation, we explore Meredith’s work in the field of public interest technology, and her view of the relationship between technology and artificial intelligence.”

“In this paper, Edward and his team explore the use of adversarial transfer attacks and how they’re able to lower their success rate by simulating class disparity.”

“The complete show notes for this episode can be found at twimlai.com/go/528.”

“The complete show notes for this episode can be found at twimlai.com/go/514.”

“The article doesn't contain a direct quote.”

“We explore the paper Skip-Convolutions for Efficient Video Processing, which looks at training discrete variables to end to end into visual neural networks.”

“The article doesn't contain a direct quote.”

“Interpretability is often a deciding factor when a machine learning (ML) model is used in a product, a decision process, or in research.”

“The article doesn't contain any direct quotes.”

“Daan walks us through some of the challenges on both the modeling and engineering sides of building the platform, as well as the inherent challenges of video applications.”

“The complete show notes for this episode can be found at twimlai.com/go/422.”

“In our conversation with Shakir, we discuss his recent paper ‘Decolonial AI,’ the distinction between decolonizing AI and ethical AI, while also exploring the origin of the Indaba, the phases of community, and much more.”

“We were first introduced to Sasha’s work through her paper on ‘Visualizing The Consequences Of Climate Change Using Cycle-consistent Adversarial Networks’”

“Visit twimlai.com/blacklivesmatter for resources to support organizations pushing for social equity like Black Lives Matter, and groups offering relief for those jailed for exercising their rights to peaceful protest.”

“In our conversation, we discuss diversification of NeurIPS, with groups like Black in AI, WiML and others taking huge steps forward, trends in the fairness community, quite a few papers, and much more.”

“The show notes for this episode can be found at twimlai.com/talk/333/, where you’ll find links to both of these papers!”

“This episode is best consumed by watching the corresponding video demo, which you can find at twimlai.com/talk/324.”

“Thanks to Luke and Dotscience for their sponsorship of this Democast and their continued support of TWIML.”

“N/A”

“The article doesn't contain a direct quote, but the focus is on the experiences of the panelists.”

“The article doesn't contain a direct quote.”

“Hear how use cases can strategically guide platform development, the evolving relationship between her team and Michelangelo (Uber’s ML Platform) and much more!”

“Hear him discuss the challenges (and joys) of working in the industry, his insight into analyzing scale when innovation is happening in parallel with development, his experiences at Facebook, Google, and Cruise, and his predictions for the future of ML platforms!”

“The article doesn't contain a direct quote, but summarizes the key points of the interview.”

“The article doesn't contain a direct quote.”

“A game-like platform that channels the convictions of individuals to come to a consensus and using a behavioral neural network trained on people’s behavior called ‘Conviction’, to further amplify the results.”

“Hear Gary discuss his latest book, ‘Rebooting AI: Building Artificial Intelligence We Can Trust’, an extensive look into the current gaps, pitfalls and areas for improvement in the field of machine learning and AI.”

“In this episode, we discuss his paper: “DeepQB: Deep Learning with Player Tracking to Quantify Quarterback Decision-Making & Performance”, what it means for football, and his excitement for machine learning in sports.”

“Lotte discusses her paper, ‘Choke or Shine? Quantifying Soccer Players' Abilities to Perform Under Mental Pressure’ and the implications of her research in the world of sports.”

“The article doesn't contain a direct quote, but it focuses on the discussion of experiment tracking and the Weights & Biases tool.”

“Olivier joins us to discuss his work on Google’s research football project, their foray into building a novel reinforcement learning environment.”

“The article doesn't contain a direct quote.”

“Anubhav explains the design of a system that takes the literature and uses natural language processing to conceptualize complex material science concepts.”

“Cynthia explains black box and interpretable models, their development, use cases, and her future plans in the field.”

“The article doesn't contain a direct quote, but the focus is on Dr. Darling's research and insights.”

“The article doesn't contain a direct quote, but it discusses the research and methods used.”

“Theo’s research is focused on brain circuit development and uses Deep Learning methods to segment the brain regions, then detect the connections around each region.”