Twitter/X Releases OSS Grok The internet has been discussing the release of Twitter / X's contender in the ChatGPT race with xAI: This comes as the latest release for a tech giant foundation model from X/Twitter with the release of Grok-1. This ML system was developed across four months, and has been published with open benchmarks that showcase performance better than GPT 3.5 and Llama 2.0 - although it's performance is not better than GPT 4.0, being an open-weights release it makes it a fantastic contribution. The team is exploring research avenues to address AI limitations and is offering early access to Grok in the US to gather feedback for further improvements. |
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Mamba State Space Architecture Mamba is the novel "state space" architecture that is taking transformers head-first with a promise of parallel computation benefits: The state-space architecture uses input-dependent dynamic state space matrices and Zero-Order Hold, which enables for long-term memory as well as highly-parallel processing capabilities, which tackles the limitations of several sequence modeling techniques of traditional RNNs and transformers. |
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Microsoft GenAI Online Lessons Microsoft's releases a set of Generative AI resources for Beginners, providing an 18-lesson program designed for production machine learning practitioners: This great resource offers a comprehensive introduction to building Generative AI applications, covering a broad spectrum of topics beyond the basics, including advanced LLM application development. This course encompasses text generation, image generation, chat applications, and AI security. |
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An Intro to SQL for Scientists An Introduction to SQL for Weary Data Scientists: A great resource for practitioners and educators to demystify SQL with a comprehesive set of examples, and a wide range of topics. This resource covers the full end-to-end of SQL - from basic database management to advanced SQL functionalities like joins, window functions, and JSON data manipulation. The course also includes downloadable content for practical exercises which can serve both self-learners as well as instructors that want to leverage SQL resources. |
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Forecasting Principles & Practice The go-to resource to build strong practical foundations on forecasting is Rob Hyndman's free book "Forecasting: Principles & Practice". This free online textbook provides one of the most complete and comprehensive introducitons to forecasting methods. This edition introduces new content and reorganizes chapters for better understanding of time series analysis before forecasting. It is quite refreshing to see real-world data to teach forecasting, incorporating the latest methodologies and corrections based on feedback, whilst staying true to the key foundations that are key to build upon amid the many ongoing trends in machine learning. |
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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. Upcoming conferences where we're speaking:
Other upcoming MLOps conferences in 2024:
In case you missed our talks:
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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. - Kompute - Blazing fast, lightweight and mobile phone-enabled GPU compute framework optimized for advanced data processing usecases.
- CuPy - An implementation of NumPy-compatible multi-dimensional array on CUDA. CuPy consists of the core multi-dimensional array class, cupy.ndarray, and many functions on it.
- Jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
- CuDF - Built based on the Apache Arrow columnar memory format, cuDF is a GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data.
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! |
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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: - MLSecOps Top 10 Vulnerabilities - This is an initiative that aims to further the field of machine learning security by identifying the top 10 most common vulnerabiliites in the machine learning lifecycle as well as best practices.
- AI & Machine Learning 8 principles for Responsible ML - The Institute for Ethical AI & Machine Learning has put together 8 principles for responsible machine learning that are to be adopted by individuals and delivery teams designing, building and operating machine learning systems.
- An Evaluation of Guidelines - The Ethics of Ethics; A research paper that analyses multiple Ethics principles.
- ACM's Code of Ethics and Professional Conduct - This is the code of ethics that has been put together in 1992 by the Association for Computer Machinery and updated in 2018.
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!
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The Institute for Ethical AI & Machine Learning
