Issue #252 - The ML Engineer
Alejandro Saucedo
AI & Data Executive @ Zalando | Advisor @ UN, EU, ACM, etc | Join 70k+ ML Newsletter
If you like the content please support the newsletter by sharing with your friends via ?? Email, ?? Twitter, ?? Linkedin and ?? Facebook! If you've come across this you can join the newsletter? for free at https://ethical.institute/mle.html ?
(PS. the image was generated using GPT-4V Stable Difussion 3.0)
The ML Engineer this week:
Thank you for being part of over 50,000+ ML professionals and enthusiasts who receive weekly articles & tutorials on Machine Learning & MLOps ?? You can join the newsletter for free at https://ethical.institute/mle.html ?
If you are a Machine Learning Practitioner looking for an interesting opportunity, I'm currently hiring for a few roles including Applied Science Manager, Applied Scientist, Analytics Team Lead, and Customer Analyst - do check it out and do feel free to share broadly!
Chip Huyen has put together a comprehensive overview of Multimodality and Large Multimodal Models. The article delves into the rise of LLMs that operate beyond single data modalities, marking a shift from traditional ML models limited to text, image, or even audio. This article covers quite an extensive case for the potential of multimodality in LLMs following from DeepMind's recent GPT4V release. The article dives into: 1) exploring multimodality's context, 2) discussing fundamental multimodal systems like CLIP and Flamingo, and 3) highlighting ongoing research areas in LMMs such as efficient training techniques + new systems like BLIP-2 and LLaVA.
The State of AI Report for 2023 is out: This edition discusses key trends like GPT-4's surprise to the world, the efforts to mimic proprietary model performance, and real-world breakthroughs driven by Language Models and diffusion models in life sciences. The report also highlights the booming compute industry led by NVIDIA, the rise in generative AI startups amidst a tech valuation slump, and the ongoing global safety debate concerning AI, emphasizing the necessity for robust evaluations of state-of-the-art models.
A great resource to build a strong intuition on the fundamentals of Stable Difussion by building it from scratch. This video covers a deep dive starting with foundational concepts, including the intricacies of generative models, the mathematics behind them, and their applications, including text-to-image, image-to-image, and inpainting processes. You can also access the repository and the PDF slides.
Transformer-based forecasting continues to see insightful developments, this time from Tsinghua University researchers on an inverted transformer architecture. This is an interesting development similar to the TSMixer architecture that Google released a few months ago. This "iTransformer" architecture leverages an inverted which instead of treating each time step as a token, it embeds the entire variable history as individual tokens, addressing the typical Transformer limitations in this domain. It is suggested that this better captures multivariate correlations and encodes temporal series representations.
A fantastic book providing an in-depth introduction to modern statistics with great accompanying resources, and for free (with a pay-what-you-wish option)! This v2 resource is in progress but with the first edition available online covering a broad range of topics including data introduction, exploratory data analysis, regression modeling, foundations of inference, statistical inference, and inferential modeling. The textbook comes with supplementary materials like slides, labs, and interactive tutorials, which would be useful for practitioners aiming to enhance their understanding of modern statistics in the context of production machine learning.
领英推荐
Upcoming MLOps Events
The MLOps ecosystem continues to grow at break-neck speeds, making it ever harder for us as practitioners to stay up to date with relevant developments. A fantsatic way to keep on-top of relevant resources is through the great community and events that the MLOps and Production ML ecosystem offers. This is the reason why we have started curating a list of upcoming events in the space, which are outlined below.
Check out our "MLOps Curriculum" from previous conferences:
Relevant upcoming MLOps conferences:
Open Source MLOps Tools
Check out the fast-growing ecosystem of production ML tools & frameworks at the github repository which has reached over 10,000 ? github stars. We are currently looking for more libraries to add - if you know of any that are not listed, please let us know or feel free to add a PR. Four featured libraries in the GPU acceleration space are outlined below.
If you know of any open source and open community events that are not listed do give us a heads up so we can add them!
OSS: Awesome AI Guidelines
As AI systems become more prevalent in society, we face bigger and tougher societal challenges. We have seen a large number of resources that aim to takle these challenges in the form of AI Guidelines, Principles, Ethics Frameworks, etc, however there are so many resources it is hard to navigate. Because of this we started an Open Source initiative that aims to map the ecosystem to make it simpler to navigate. You can find multiple principles in the repo - some examples include the following:
If you know of any guidelines that are not in the "Awesome AI Guidelines" list, please do give us a heads up or feel free to add a pull request!
About us ?
The Institute for Ethical AI & Machine Learning is a UK-based research centre that carries out world-class research into responsible machine learning.