We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Machine Learning
The landscape of machine learning in the Elixir programming language is diverse and rapidly evolving, with an emphasis on functional programming and powerful concurrency primitives. The Nerves Project, although primarily focused on embedded systems, has seen updates that might contribute to machine learning applications in edge devices. Within this landscape, the FLAME library and Nx are being discussed as formidable tools for constructing elastic workloads, challenging the norms of serverless computing.
Leveraging the strengths of Elixir's functional environment, libraries such as Axon have been developed, offering a fresh perspective to neural network training by providing an Elixir-native API without the need for bridging to Python-based frameworks. This approach not only simplifies machine learning workflows but also enhances scalability. Elixir is also proving itself to be nimble in startup times for machine learning applications, with strategies like Dockerfile caching dependencies, driving faster deployments.
When it comes to integrating AI into Elixir projects, open-source initiatives like Instructor pave the way by addressing common integration challenges such as parsing unstructured data. By utilizing Ecto schemas, Instructor aims to streamline AI integration into standard software systems. Additionally, a variety of Elixir libraries are making machine learning more approachable, with each offering distinct functionalities likened to their Python counterparts. These libraries, including Elixir-Nx, Axon, Bumblebee, and Scholar, enrich the ecosystem with tools for data exploration, model training, and application in real-world apps like semantic search for HexDocs.
Moreover, enhancements in Phoenix reveal an intersection with AI through features such as image recognition and conversational agents, highlighting the flexibility of Elixir in various domains. The language's ecosystem is seen to mature with developers reflecting on its growth particularly in machine learning, underlining projects like Nx that began with unlikely starts but now face a promising future. The practical application of machine learning in Elixir spans several domains, from optimizing language models to developing audio-speech recognition with pre-trained models.
Elixir's vibrant community is contributing to a wealth of educational materials, podcasts, and conferences, where topics range from prototyping AI agents and full-text search engines to using fuzzy logic and machine learning for real-world problems like spam detection. Thought leaders and developers alike are demonstrating the applicability and efficiency of Elixir in machine learning through tutorials, real-world applications, and explorations of model deployment in production environments. The broad and active involvement in areas such as conversational AI, recommendation engines, and prototyping evidences a keen interest in leveraging Elixir's strengths in the AI field. The growing library ecosystem and improvements in areas like quantization and MLIR support promise an exciting future for machine learning applications within the Elixir community.
Creating Custom Elixir Copilots through Model Fine-Tuning
Sean Moriarity discusses the process of fine-tuning a personal Elixir code completion model using the Hugging Face's transformers library and Elixir's machine learning capabilities.
Creating a Text-to-Speech Service Using Elixir Without Paid Third-Parties
The author thedangler is seeking advice on creating a local text-to-speech service similar to ElevenLabs, utilizing Elixir and pre-trained models without relying on paid third-party services.
Enhancing Elixir with Enumerable Protocol and Sigils for Intervals
Andrés Alejos offers a detailed look at adding support for real-valued intervals implementing the Enumerable Protocol in Elixir through a custom library called Exterval.
Elixir Programming Updates and Community News
This episode covers the latest updates in the Elixir community, including the release of Elixir 1.16.0 and Machine Learning ecosystem developments.
Transition from Python Data Analysis to Elixir: A Case Study on Statistical Calculations
Written by Herminio Torres, this article talks about a journey from Python Data Analysis to exploring the Elixir Challenge with Nx and building a Mean-Variance-Standard Deviation Calculator.
Chris McCord Introduces FLAME for Phoenix in Thinking Elixir Podcast
Chris McCord discusses the announcement of FLAME in the Thinking Elixir Podcast, which brings a new serverless approach to the Phoenix framework.
Adoption of Elixir at Amplified: Productivity and Cost Benefits
In a detailed conversation, Chris Grainger, CTO of Amplified, shares his journey of adopting Elixir for his company, transitioning from Python and other languages. He discusses the significant benefits of Elixir's functional programming, LiveView, and the integration of Nx and ONNX. This shift led to remarkable improvements including halved AWS bills and reduced development team size while achieving more work.
Discussion on 'Machine Learning in Elixir' Book
Sean Moriarity announces the release of a new book, 'Machine Learning in Elixir,' which aims to educate readers on leveraging Elixir and the Nx library for practical machine learning tasks, including computer vision and natural language processing.
Elixir Implementation of Machine Learning Book via Nx and Axon Livebooks
NickGnd shares an Elixir-based implementation of 'Programming Machine Learning' using Livebooks, Nx, and Axon.
Implementing Machine Learning with Elixir on Fly.io GPUs
Jason Stiebs provides an overview of using GPUs on Fly.io for real-world machine learning applications with Elixir, focusing on the implementation of a semantic search for Elixir's HexDocs.
Elixir's Practicality and Potential Beyond Web Development
Jason Stiebs touched on the practicality and power of Elixir, especially for web development and beyond. He recognized Elixir's leverage as an efficient, production-ready language with a solid ecosystem including Phoenix and observed a relative stability in his tech stack over years. He advocated for exploring Elixir's capabilities outside the traditional web domain, citing examples from machine learning to 3D modeling.
Translating Python NumPy Code to Elixir-Nx
Andrés Alejos presents an insightful article on converting Python's NumPy machine learning code to Elixir's Nx library.
Exploring AI Integration in Elixir with Sean Moriarity
In episode 154 of the Thinking Elixir Podcast, the hosts discuss the intersection of AI and the Elixir programming language with special guest Sean Moriarity.
Exploring Elixir's Interaction with WebAssembly through Orb
This episode of the Thinking Elixir Podcast discusses the Orb project, created by Patrick Smith, which is an Elixir DSL for WebAssembly and how it can be integrated into LiveView for improved user experiences.
Exploring Machine Learning's Evolution with Elixir Featuring Sean Moriarity
Sean Moriarity discusses the impact and future of Elixir in machine learning (ML) and artificial intelligence (AI), detailing the various technologies involved and highlighting the advantages of using Elixir for ML applications.
Discussion on Elixir's Future with José Valim
José Valim, creator of Elixir, talks about the language's future developments, community involvement, and hints at a potential typing system.
Discussions on Phoenix and Its Future Developments
Phoenix core team members Chris McCord and Jason Stiebs discuss key updates and future prospects of the Phoenix and LiveView with Elixir Wizards hosts Sundi Myint and Owen Bickford.
Discussion on Haystack Full-Text Search Engine in Elixir
Philip Brown, an Elixir software engineer, joins the Elixir Mix podcast to discuss Haystack—a full-text search engine created using Elixir.
Elixir Developer Experiences and AI in Elixir
In this episode of 'Elixir Mix,' the panelists Adi Iyengar, Allen Wyma, and Sascha Wolf discuss their recent experiences and challenges while working on Elixir projects and the value of AI in the Elixir ecosystem.
Discussing Elixir and Machine Learning with Sean Moriarity
In this episode of Beam Radio, the hosts engage in a conversation with Sean Moriarity about the intersection of machine learning and Elixir programming.
Integrating Fuzzy Logic into Elixir for Intelligent Decision-Making
Aldebaran Alonso presents a talk on the application of Fuzzy Logic in Elixir projects, enhancing Elixir applications with human-like decision-making capabilities.
Comparing Machine Learning Capabilities Across Elixir, Python, SQL, and Matlab
Katelynn Burns and Alexis Carpenter discuss the state of machine learning in Elixir compared to Python, SQL, and Matlab in a recent Elixir Wizards podcast episode.
Quick Neural Network Training with Elixir & Axon
Sean Moriarty demonstrates the speed and simplicity of training a neural network using Elixir and Axon, leveraging Livebook for an interactive coding experience.
Elixir vs Python in Neural Network Performance and Development Experience
A. Neto and L. C. Tavano delivered a presentation on the comparison between Elixir and Python in terms of development experience and performance while working with simple neural networks.
Exploring Firmware Design in Embedded Systems with Elixir
Jon Carstens delivers a presentation on firmware design, focusing on its relationship with hardware and software and the role it plays in the development for embedded systems. He advocates for the relevance of firmware in a world increasingly dominated by smart devices and embedded technology.
Exploring Machine Learning in Elixir with a Recommendation Engine
Andrew Forward discusses the potential for using Elixir to build a recommendation engine for a gifting platform. He explores traditional machine learning algorithms such as KNearestNeighbour, (Naive) Bayes, and KMeans, and introduces the Elixir library 'scholar' for implementing these algorithms.
Elixir as the Language of Choice for Large Language Models
Sean Moriarty discusses the challenges and opportunities presented by large language models (LLMs) and advocates for Elixir as an ideal language for developing LLM-powered applications.
Leveraging Elixir & Phoenix for Building Software in Auroville
Shankar Dhanasekaran speaks about using Elixir and Phoenix to create software for Auroville, a city of 50,000 people. He emphasizes the benefits of Elixir and Phoenix in managing complex, multi-service domains, and shares their journey of moving away from Drupal to Elixir, the adoption challenges faced, and the productivity gains. The talk also highlights the future potential of Elixir in the context of Auroville's development, such as the potential for cloud farming and machine learning.
Enhancing LiveView with Membrane for Realtime Media Processing
Lars Wikman, the founder of Underjord and a member of the BEAM Radio team, presents how the Membrane Framework can enhance LiveView with live video and audio capabilities. He discusses potential applications and the excitement of creating cool things by combining different inputs, transformations, and outputs.
Bringing Machine Learning Capabilities into Elixir with Bumblebee
Jonatan Klosko presents Bumblebee, an Elixir tool that simplifies using pre-trained machine learning models.
Insights on Elixir Development and Learning Experience
José Valim presents a keynote speech on updates and the future of Elixir, including development and learning experience enhancements.
Elixir's Impact on Machine Learning and Production Workflows
Christopher Grainger explores the integration of machine learning in production within the Elixir ecosystem, highlighting the use of Nx, Livebook, and Scholar.
Three-Year Growth of Elixir's Nx Machine Learning Library
Sean Moriarity reflects on the growth and success of the Elixir machine learning ecosystem over the past three years. He discusses the unlikely start of the Nx project, the challenges faced, and the future of machine learning in Elixir.
Developing a Chessboard Image to FEN Converter with Elixir
Barrett Helms presents at ElixirConf 2023 about building an image recognition system in Elixir that converts pictures of a chessboard into Forsyth-Edwards Notation (FEN) for efficient storage and renders an interactive board in the UI. Through his talk, Barrett shares his journey of encountering the problem while building a web app for practicing chess tactics and finding a solution using Elixir.
Optimizing and Serving Large AI Models with Elixir and Nx
Toran Billups fine-tunes Mistral 7B using the RTX 4090 with limited vRAM, thanks to the open source Python project lit-gpt. He shares the steps required for fine-tuning and serving the model with Nx.
Building Scalable Machine Learning Applications with Elixir
Sean Moriarity shows how easy it is to build machine-learning applications with Elixir, especially in a few hours, to build a simple enriched newsfeed.
Using Elixir's Axon for Custom Language Model Training
Toran Billups explores the key aspects of fine-tuning language models with Axon and Bumblebee at ElixirConf 2023, covering topics from data engineering and model selection to optimization techniques and evaluation strategies.
Summary of Machine Learning Developments in Elixir for Q3 2023
José Valim explores the latest developments in Elixir and Machine Learning in his blog post, highlighting the improvements in Nx, Explorer, Bumblebee, Scholar, and other projects. The future looks bright as optimization areas, like quantization and MLIR support, gain further attention.
Integrating Machine Learning Models with Elixir Using Nx
Andrés Alejos presents a talk at ElixirConf 2023 about using EXGBoost + Mockingjay, a Gradient Boosted Decision Tree library, in Elixir for learning structured tabular data and its application in a scalable production environment using Nx's Serving capability and a Phoenix web app.
Streamlining MLOps with Elixir's Capabilities
Sean Moriarity shows how to do MLOps in Elixir, simplifying the deployment of machine learning models without much effort.
Enhancing Machine Learning Decision Trees with Elixir
Andres Alejos created Mockingjay, a library designed to implement algorithms present in Microsoft’s Hummingbird for compiling tree-based machine learning algorithms into native Nx functions.
Developing AI Applications Using Elixir
Charlie Holtz discusses prototyping and deploying AI agents with Elixir, highlighting the benefits of using the BEAM + Elixir Agents for building specialized AI models and applications in a distributed, functional, and scalable manner.
Exploring Motion Tracking in Elixir with Bumblebee and LiveView
Katelynn Burns presents the Thursday keynote at ElixirConf US 2023, Orlando, FL. She explores the fascinating and complicated movement of bodies, discussing how LiveView's open socket design and Bumblebee's neural network capability can be used to create motion magic.
Insights and Lessons from Phoenix Framework Development
Chris McCord shares his insights on new features coming to Phoenix at ElixirConf US 2023 in Orlando, FL.
Improving Elixir Argument Validation with NimbleOptions
Andres C Alejos discusses how to level up your Elixir option handling with the NimbleOptions library, which provides powerful and flexible argument validation schemas.
Serving Spam Detection With XGBoost and Elixir
Learn how to detect spam with XGBoost and Elixir and serve the model for production use. Andres C Alejos shares their process and insights in this informative article.
Exploring Flop for Elixir Data Handling
In Episode 166 of the Thinking Elixir podcast, Mathias Polligkeit discusses his creation of the flop library, which provides a convenient and reusable solution for filtering, sorting, and pagination in Elixir projects. He also introduces the flop_phoenix package, which includes heex components for building filter forms and tables. It's an interesting exploration of a useful library for Elixir developers.
Using Whisper for Speech Recognition in Elixir Applications
In this blog post, Sean Moriarity introduces Whisper, an audio-speech recognition model developed by OpenAI. He explains the challenges and uses of audio-speech recognition and provides instructions on how to use Whisper in Elixir applications with the help of the Bumblebee library.
Using Scholar for Traditional Machine Learning in Elixir
Sean Moriarity discusses traditional machine learning in Elixir with Scholar, a set of machine learning tools built on top of Nx. He explains how Scholar offers implementations of non-deep-learning models like linear regression and logistic regression, and demonstrates how to fit and visualize a linear regression model using Scholar in Elixir.
Elixir and Open-Source Alternatives to Proprietary LLMs like ChatGPT
In this blog post by Sean Moriarity, he discusses the rise of large-language models (LLMs) like OpenAI's ChatGPT and GPT-4, and explores open-source alternatives to these models. He highlights the benefits of using open-source models, such as data privacy, lower latency, task-specific performance, and cost considerations, and introduces some popular open-source options like Flan-T5, Llama, and OpenAssistant that can be used with Elixir.
© HashMerge 2024