Tarides | Internship Report: Refactoring Tools Coming to Merlin
Timéo shares his project integrating new refactoring features into Merlin, improving user experience with a new command.| tarides.com
Software is designed for the average customer, but the truth is that no customer is the actual average. That’s why we’re always dealing with trade-offs. Our tool process flow doesn’t quite match the reality of our business. The analytics dashboard doesn’t quite capture the right... The post You Are Not The Average Customer appeared first on InterWorks.| InterWorks
So, you build a great predictive model. Now what? MLOps is hard. Deploying a model involves different tools, skills, and risks than model development. This dooms some data science projects to die on their creator’s hard drive. Tools like dbt and SQLMesh entered the scene to solve a similar problem for data analysts. These tools offer an opinionatee frameowrk for organizing multiple related SQL scripts into fully tested, orchestrated, and version conotrolled projects. Data analysts can deliv...| Emily Riederer
Timéo shares his project integrating new refactoring features into Merlin, improving user experience with a new command.| tarides.com
A simple way to encode dependency injection using the Reader monad and objects in OCaml (to work well with type inference).| gr-im.github.io
[ML'23] Modernizing Standard ML of New Jersey: A Status ReportDavid MacQueen, John ReppyThis paper describes our ongoing efforts to modernize the Standard ML...| YouTube
Typecheckers built for fun| sdiehl.github.io
An important aspect of OCaml that newcomers might want to| kirancodes.me
A detailed explanation of why I chose OCaml as the ‘default’ programming language for every project.| xvw.lol
0.0: Welcome| saityi.github.io
GT2 Pro members, download a high-res version of this image that you can use royalty-free anywhere:| Good Tech Things
Posit’s recently-announced project orbital translates fitted SciKitLearn pipelines to SQL for easy prediction scoring at scale. This project has many exciting applications to deploy models for batch prediction with near-zero dependencies or custom infrastructure and have scores accessible to operatilize from their data warehouse. As soon as I heard about the project, I was eager to test it out. However, much of my recent work is in pure xgboost and neither xgboost’s learning API nor the s...| Emily Riederer
A number of airline turbulence events have recently made global media headlines, leaving travelers wondering what, if anything, can be done to reduce their own risk. Carriers are required by law to turn the seatbelt sign on during takeoff and landing, but policies on using the sign during flight can vary from airline to airline. […] The post Turbulence and Airline Flights: Is the Threat from Rough Air on the Rise? appeared first on Connected Aviation Today.| Connected Aviation Today
A Bitter Take on Final Fantasy IX’s Card Game| xvw.lol
A popular meme in the world of PL’s is that “Haskell has monads”, with the implication that this is a distinctive feature of the language, separate from all others. While it is t…| Existential Type
Dark Inc has officially run out of money. Dark Inc is the company we founded in 2017 to build Darklang, a statically-typed functional programming language built to strip all of the bullshit from backend coding. To ensure continuity for users and fans, as well as to continue building what we| Darklang
OxCaml’s primary design goals are:| oxcaml.org
We upgraded Semgrep from OCaml 4 to OCaml 5 and have open-sourced a garbage collector tuning utility that allowed us to make the upgrade with negligible performance changes.| Semgrep
Ever feel like your AI tools are a bit...well, passive? Like they just sit there, waiting for your next command? Imagine if they could take initiative, break down big problems, and even work together to get things done. That's exactly what LLM agents...| freeCodeCamp.org
The post OCI-SIF Container Images: Unraveling Their Features and Benefits appeared first on Sylabs.| Sylabs
The post Sylabs Launches the Singularity Containers Certification appeared first on Sylabs.| Sylabs
The post Sylabs Announces SingularityCE 4.1.0 with Enhanced Docker Integration and Advanced User Autonomy appeared first on Sylabs.| Sylabs
Attention powers “transformers” - the seemingly complex architecture behind large language models (LLMs) like ChatGPT. But what does attention even mean?| Maharshi's blog
I’m tired of this phrase and this simple way of thinking about tools. This blog post is a wandering train of thought on the topic of what tools are and why it matters to be even slightly more mature in how we think about them.| Frank Elavsky
KASIKORN Business-Technology Group (KBTG) Labs and Muang Thai Insurance PCL have partnered to use machine learning (ML) technology.| Govindhtech
What really is the color GREEN? What does it mean to different people? We actually have no idea. Now, consider The Dress on its 10 year anniversary. One can either argue with others whether it is BLUE and BLACK or WHITE and GOLD, or objectively look at it’s composition from a technical standpoint. Below is … Continue reading Subjectivity and Perception| GeoEnergy Math
https://huggingface.co/ehartford/based-30b So, as I was working on Wizard-Vicuna-30b-Uncensored and WizardLM-Uncensored-Falcon-7b, I came to the realization that these models, despite being trained with no refusals, were still refusing. How could thi...| Cognitive Computations
I asked GPT-4 to respond to my previous article "Uncensored Models" because it is more likely to provide civil discourse rather than the shrill demagoguery that my human opponents have tended to employ. I found it interesting and both sides have vali...| Cognitive Computations
Can we guide an Artificial Intelligence to self-select tasks based on internal "wants" or desires?| Nick Yoder
In this article, I review the Foundations of AI and Machine Learning for Java Developers video course from Frank Greco.| Vlad Mihalcea
In this blogpost we want to introduce the topic of using a Large Language Model (LLM) as an evaluator — a novel approach to tackling the complexities of evaluating advanced machine learning systems, particularly in tasks like Automatic Summarization, Text Generation, and Machine Translation, where traditional metrics struggle to capture nuances like cross-lingual accuracy and bias detection.| blog.allegro.tech
Is Rust a contender for ML projects?| Tempus Ex
Why do frame pointers matter for OCaml?| lambdafoo.com
In a recent 3Blue1Brown video series on transformer models, Grant Sanderson posed a fascinating question: How can a relatively modest embedding space of 12,288 dimensions (GPT-3) accommodate millions of distinct real-world concepts? The answer lies at the intersection of high-dimensional geometry and a remarkable mathematical result known as the| Nick Yoder
A climate science breakthrough likely won’t be on some massive computation but on a novel formulation that exposes some fundamental pattern (perhaps discovered by deep mining during a machine learn…| GeoEnergy Math
This article explains how machine learning can solve problems in natural language processing and text analytics and why a hybrid ML-NLP approach is best.| Lexalytics
Data analysis of millions of GitHub events to track developer activity and tech trends driving the evolution of open-source WebRTC| webrtcHacks
(disclaimer: This article is also for OCaml developers, but I use F# as it is the language that I currently learning)| rm4n0s.github.io
Dmitrii Kovanikov's Personas Web Space| Dmitrii Kovanikov aka chshersh
What are the day-to-day benefits of functional programming?| functionalsoftware.se
I’ve been a programmer since the age of 8, and some kind of developer for most of my life. Throughout my life as a coder, both hobbyist and professional, I’ve learnt plenty of programming languages that felt like cookie-cutter clones of each other, but also a few programming languages that changed the way I looked at programming, sometimes even at thinking.| Il y a du thé renversé au bord de la table !
A fable about a company's journey through scaling their ML function, and some practical advice on how you should do it| Alexandru Burlacu
A foundation model is a type of artificial intelligence neural network trained on vast amounts of raw data, typically through unsupervised learning, and designed to be adaptable for a wide range of tasks. In a new paper Apple Intelligence Foundation Language Models, an Apple research team introduces the foundation language models developed to power Apple| Synced
Robot learning has seen remarkable advancements in recent years; however, achieving human-level performance in terms of accuracy, speed, and adaptability remains a significant challenge across various domains. One such domain is table tennis—a sport that demands years of rigorous training for human players to reach an advanced level of proficiency. In a new paper Achieving| Synced
Video captioning is essential for enhancing content accessibility and searchability by providing precise and searchable descriptions of video content. However, the task of generating accurate, descriptive, and detailed video captions remains challenging due to several factors: the limited availability of high-quality labeled data and the additional complexity involved in video captioning, such as temporal correlations| Synced
In natural language processing (NLP) applications, long prompts pose significant challenges, including slower inference speed, higher computational costs, and a diminished user experience. Furthermore, the limitations imposed by context length restrict model performance and application scope, creating a strong need to reduce prompt length. In a new paper 500xCompressor: Generalized Prompt Compression for Large Language| Synced
The homepage of opam, a package manager for OCaml| opam.ocaml.org
Renting a GPU in the cloud, especially with a bare-metal host can be expensive, and even if the hourly rate looks reasonable, over the course of a year, it can really add up. Many of us have a server or workstation at home with a GPU that can be used for serving models with an open source project like Ollama.| inlets.dev
Predictions 2023: What's coming next in enterprise technology - SiliconANGLE| SiliconANGLE
Several Large Language Models are emerging: Google Bard/LaMDA, Meta's LLaMA, Amazon's Multimodal-CoT, HuggingFace's Bloom, and open-source ChatLLaMA.| Machine Learning for Developers
ChatGPT is part of OpenAI's GPT-3 family of large language models. It is immensely powerful but can confidently hallucinate too. Here is what ChatGPT can and can't do.| Machine Learning for Developers
Should you choose an all-in-one MLOps platform from your cloud provider or cobble together a solution from piecemeal tools?| Machine Learning for Developers
AI research continues to amaze us, but are those safe to use in products and services? Concerns about AI aligning with human goals have become real.| Machine Learning for Developers
Data pipelines transport data to the warehouse/lake. Machine Learning pipelines transform data before training/inference. MLOps pipelines automate ML workflows.| Machine Learning for Developers
Survey of data science and machine learning lifecycle from resource-constrained batch data mining era to current MLOps era of CI/CD/CT at the cloud scale.| Machine Learning for Developers
Overview of MLOps, ML Pipeline, and ML Maturity Levels for continuous training, integration, and deployment.| Machine Learning for Developers
The Feature Platform for Machine Learning, from the creators of the Uber Michelangelo feature store| Tecton
Explore the roles of embeddings, RAG, ETL, and LLM-powered feature pipelines in developing robust Next-Gen fraud detection mechanisms.| Markovate
TEN18 by Exabeam breaks down their blueprint for leaders facing the many cybersecurity challenges created by mergers and acquisitions.| Exabeam
Transformers have fundamentally transformed the field of natural language processing, driving significant advancements across numerous applications. With their widespread success, there is a growing interest in understanding the complex mechanisms of these models. One key aspect that has not been thoroughly examined is the inherent linearity of intermediate embedding transformations within transformer architectures. In a| Synced
The field of medical artificial intelligence (AI) is advancing rapidly, heralding a new era of diagnostic accuracy and patient care. Researchers have been focusing on developing AI solutions for specific tasks, but current medical AI systems are often limited to narrow applications, hindering their broader adoption in clinical practice. In face of this limitation, in| Synced
Large language models (LLMs) have demonstrated remarkable proficiency in various natural language tasks and an impressive ability to follow open-ended instructions, showcasing strong generalization capabilities. Despite these successes, a notable limitation of LLMs is their inability to perceive non-textual modalities such as audio. In a new paper SpeechVerse: A Large-scale Generalizable Audio Language Model, a| Synced
In various domains, Diffusion Models (DMs) have emerged as groundbreaking tools, offering an unparalleled blend of realism and diversity while ensuring stable training. However, their sequential denoising process poses significant challenges, being time-consuming and costly. In a new paper Imagine Flash: Accelerating Emu Diffusion Models with Backward Distillation, a Meta GenAI research team introduces an| Synced
The incorporation of spatially dependent variables in a machine learning model can greatly improve the model’s performance. These features can include, but not limited to: the spatial lag (neighborhood average) of a variable counts of neighboring features most common category nearby spatial embedding via principle coordinate analysis Deriving spatial features These kinds of spatial variables are dependent upon the features nearby them. To calculate these variable one needs to have a concept...| Josiah Parry
I want to write about fine-tuning Alpaca 30b 4-bit on consumer hardware, but before I can, I'll need to give a little background. My basic goal was to figure out "what's the most powerful AI I can customize and run on my shiny new 4090." The answer r...| Cognitive Computations
Achieving excellence across diverse medical applications presents significant hurdles for artificial intelligence (AI), demanding advanced reasoning abilities, access to the latest medical knowledge, and comprehension of intricate multimodal data. Gemini models, Google's cutting-edge AI, stand out for their robust general capabilities in multimodal and long-context reasoning, presenting promising avenues in the realm of medicine. In| Synced
Multi-layer perceptrons (MLPs) stand as the bedrock of contemporary deep learning architectures, serving as indispensable components in various machine learning applications. Leveraging the expressive power conferred by the universal approximation theorem, MLPs excel in approximating nonlinear functions, embodying a default choice for many tasks. However, despite their widespread adoption, MLPs harbor notable limitations. They often| Synced
Ensuring that Large Language Models (LLMs) align with human values and preferences is crucial for their utility and safety. Yet, devising effective tools for this alignment presents significant challenges, particularly with the largest and most sophisticated LLMs, which often boast tens or hundreds of billions of parameters. In a new paper NeMo-Aligner: Scalable Toolkit for| Synced
GT2 Pro members, download a high-res version of this image that you can use royalty-free anywhere:| Good Tech Things
Deep reinforcement learning is a powerful technique for creating effective decision-making systems, but its complexity has hindered widespread adoption. Despite the perceived cost of RL, a wide range of interesting applications are already feasible with current techniques. The main barrier to broader use of RL is now the lack of accessible tooling and infrastructure. In […]| Clemens' Blog
The rapid progress in deep reinforcement learning (RL) over the last few years holds the promise of fixing the shortcomings of computer opponents in video games and of unlocking entirely new regions in game design space. However, the exorbitant engineering effort and hardware investments required to train neural networks that master complex real-time strategy games […]| Clemens' Blog
Within these pages are recorded my attempts to wield the highest arcane art and conjure minds that play the game of CodeCraft. Humble Beginnings As all advanced AI technologies, our tale begins with hacky plumbing that lets our game speak in the serpent’s tongue and links its fleeting worlds with magic mirrors made of chrome […]| Clemens' Blog
I spent a good chunk of my time over the last two years applying deep reinforcement learning techniques to create an AI that can play the CodeCraft real-time strategy game. My primary motivation was to learn how to tackle nontrivial problems with machine learning and become proficient with modern auto-differentiation frameworks. Thousands of experiment runs […]| Clemens' Blog
The capabilities of game-playing AIs have grown rapidly over the last few years. This trend has culminated in the defeat of top human players in the complex real-time strategy (RTS) games of DoTA 2 [1] and StarCraft II [2] in 2019. Alas, the exorbitant engineering and compute resources employed by these projects has made their replication difficult. […]| Clemens' Blog
Quickly understand inscrutable LLM frameworks by intercepting API calls.| hamel.dev
LLMs with huge context windows are here. What opportunities do they unlock?| daleonai.com
We've been working hard at Darklang for the past year, but haven't been very vocal about what we've been up to. Here’s the “Darklang” that’s been live for years: Darklang – the live version, which we're now calling Darklang classic – is a developer tool composed of a few interconnected| Darklang
After having analyzed a bunch of power metal songs to see if it was really about dragons, I wondered for a moment what could be the next step. Actually there was two next steps. The first one was to augment my power metal dataset from 58 bands to 506 bands …| Notes
Over the past ten years, Artificial Intelligence (AI) and Machine Learning (ML) have steadily crept into the Art Industry. From Deepfakes to DALL·E, the impact of these new technologies can be longer be ignored, and many communities are now on the edge of a reckoning. On one side, the potential for modern AIs to generate […] The post The Rise of AI Art appeared first on Alan Zucconi.| Alan Zucconi
Previous blog posts overviewed the MLIR dialect hierarchy for kernel code generation (CodeGen) and zoomed in on the Linalg and Vector dialects among them. Now I will switch to discuss the runtime side a bit, in order to provide a holistic view of MLIR-based machine learning (ML) compilers. This one touches the foundation and basics, including the target landscape, runtime requirements and designs to meet thereof.| Lei.Chat()
The initial blog post in this series captured my overall take on the evolution trends of compilers and IRs. It also touched on LLVM IR, SPIR-V, and MLIR, explaining the problems they are addressing and design focuses thereof. Today I will expand on MLIR and talk about its dialect hierarchy for machine learning (ML) compilers systematically.| Lei.Chat()
Vulkan (compute) has the potential to be the next-generation GPGPU standard for various GPUs to support various domains; one immediate compelling application, is machine learning inference for resource-constrained scenarios like in mobile/edge devices and for gaming. This blog post explains the technical and business aspects behind and discusses the challenges and status.| Lei.Chat()
Unique challenges for edge/mobile ML inference, contrasting with training and inference in the cloud| Lei.Chat()
Segue attended the IT Summit “MITS”, where attendees engaged with industry leaders on how automation can speed capabilities to the Air Force| Segue Technologies
Bias in AI causes machine learning-based systems to discriminate against particular groups. We investigated why AI bias occurs, and how to fight back.| Lexalytics
How to install a Caml Light development environment on DOS| www.cambus.net
OCaml with Jane Street extensions is available from our public opam repo. Only a slice of the features described in this series are currently implemented.| Jane Street Tech Blog
A discussion of the overloaded use of modules in languages| thunderseethe.dev
The first step to getting the type checker to work for you is to understand how it works, what work it can and can't do.| Practical ReScript
Find out how working on an independent research project led me to apply my MLOps skills to create a performant and cost-effective experiment infrastructure| alexandruburlacu.github.io
It’s important to be able to deploy a machine learning model when trained. But how do we approach serving ML models correctly?| alexandruburlacu.github.io
Are embeddings machine learning's most underrated but super useful tool?| daleonai.com
Using machine learning and AI to generate a fake identity online, for art and profit| daleonai.com
Everything you wanted to know about AI on Google Cloud, and much more| daleonai.com
GPU ML on Intel Arc| hillman.dev
