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dotAI 2024

machine learning engineers, mlops engineers, research scientists, data scientists, infrastructure and platform engineers, product managers, heads of AI and CTOs

multimodal language models; real-time voice agents; open-source multi-agent systems; serverless inferencing infrastructure; model quantization and edge deployment; vector databases for training; prompt engineering and output controllers; training foundation image models; data table vectorization; fairness via latent decorrelation; autoscaling and scale-to-zero; proof-search and RL pipelines

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Building with OpenAI: What's AheadRomain Huet, Katia Gil Guzman23m
Demo shows a real-time API that opens a websocket two-way stateful connection to do native speech-to-speech, multimodal I/O and function/tool calls. A live app…
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ZML: ML framework for ZigSteeve Morin13m
ZML compiles Zig model code via MLIR/XLA and Bazel into production inference artifacts that run on NVIDIA, AMD (ROCm) and TPU, with a rebuilt Torch loader and…
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Skrub: Less data wrangling, more machine learningGael Varoquaux19m
Claims that Skrub slashes the 80% data‑prep burden by providing a Python library that converts messy tables into model‑ready features, shipping a table…
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LLMs reasoning and agentic capabilities over timeStanislas Polu19m
Claim: scaled autoregressive LLMs plus a search loop and verified objective produce surprising leaps — an autoformalize + search-loop pipeline over formal…
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The future of Edge AgentsPierre Stock20m
Presents running Mistral 3B (3 billion parameters) efficiently on mobile/edge devices by mixed quantization to int8/int5 to fit in a few GB of RAM while…
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Multimodal language modelsNeil Zeghidour20m
Kyutai presents an open-source weights and code release for a compact multimodal LLM that combines a neural audio codec, a hierarchical generator and…
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Reality is not an end-to-end prediction problemInes Montani18m
Argues that prompts alone fail for production systems and shows a concrete pipeline: use spaCy llm and Prodigy for LLM-assisted annotation, transfer-learn…
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Can AI design a fairer future?Marcin Detyniecki13m
Uses the COMPAS recidivism example and an insurance pricing use case to show a concrete adversarial technique: an encoder H with HGR penalty that decorrelates…
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Training a foundation image model and deploying it to millions of usersEliot Andres20m
A custom diffusion model is trained from scratch with a bespoke dataset and architecture, running on 256 H100s and consuming energy comparable to 600 French…
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Democratizing AI with Open Source Multi-Agent SystemsSri Satish Ambati21m
Claims nightly Gaia benchmarks on an enterprise platform with Claude leading but open‑source models closing the gap, releases of 0.5B 2B 4B models trained on…
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Gain full control of your apps with Open-Source AIMerve Noyan25m
Claim: smaller open-source models often outcompete larger proprietary ones when distilled, fine-tuned and served with modern tooling. Evidence: Zier 7B hits…
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Serverless inferencing: an infrastructure point of viewYann Léger19m
Demonstrates a live deploy of Lama 3.1 on A100 with autoscaling from one to three instances and a benchmark that triggers new VMs every 15 seconds, claims real…
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More empathy and health data protection in AILaure Seugé, Arthur Talpaert15m
Doctolib announces the Consultation Assistant launch: a pipeline of signal processing, ASR, information extraction, medical summarization and coding that…
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Improving open language models at a practical sizeArmand Joulin18m
Gemma 2 ships as 2B, 9B and 27B models and claims top-in-class size-normalized performance by training small models against teacher probability distributions…
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Getting LLMs to do what you want: Output controllersMeryem Arik13m
A deterministic method called JSON DeRuLO enforces a JSON schema at inference time by applying token masking and a cheap character‑level filter so the model…
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AI is your personal co-founderMarjolaine Grondin16m
Chronicles a concrete workflow: a failed app pivoted into building an AI assistant, then automations that actually run—Zapier co-pilot for invoices, WhatsApp…
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Is Mojo programming language just a hype?Maxim Zaks11m
Mojo claims to be a practical successor for heavy compute workloads rather than mere hype: born at Modular because teams were tired of hand-writing MLIR…
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AI deployment strategies: balancing efficiency and environmental impactOri Pekelman16m
Claims that LLM apps currently emit about 0.03 megatons a day (~11 megatons/year) and that adding 2 million H100s sold this year and Grace Hoppers drives…
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Multi-agent collaboration in practice: make AI code an app for youGrigorij Dudnik09m
Claims an open source framework called Clean Coder that actually writes and updates app code is usable in production and wrote most of the startup code for…
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Rethinking AI: Building What Matters, Not Just What's PossibleAudrey Roy Greenfeld09m
A working parody-generation pipeline uses LLMs with function/tool calling, a Python class for inputs/outputs, and dual agents—a writer and editor—to generate…
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Crossing the multimodal chasmDaniel Madalitso Phiri08m
Argues that crossing the multimodal chasm requires composing smaller models into a plumbing pipeline rather than one monolithic foundation model, and shows…
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The RAod to intent-driven automationJohannes Dienst08m
Demonstrates a working JARVIS‑style system that automates UIs by translating intents into mouse/keyboard actions and evaluative checks, successfully generating…
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Message from the Secretary of State for AI and Digital AffairsClara Chappaz11m
France reports 2.5 billion euros invested since 2018 and counts over 1,000 AI startups in Paris, claims major labs and VCs have relocated here, and plans an AI…
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