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@OpenAtIntel

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Everything #opensource at Intel. We have a lot to share and a lot to learn. Join us.

Joined October 2021
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@OpenAtIntel
open.intel
6 days
Working upstream on the Linux kernel, Tony brings RAS and RDT support to Intel® Xeon® platforms, helping keep systems reliable, efficient, and ready for scale. #OpenSource #MaintainerSpotlight
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@OpenAtIntel
open.intel
7 days
Built by @laion_ai.Powered by Intel.Open to the world. Explore the datasets and try the models yourself:
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@OpenAtIntel
open.intel
7 days
EmoNet isn’t just another benchmark. It’s a new baseline for how we train AI to interpret emotion, not flatten it. It makes space for:.Real evaluation, not leaderboard chasing.Emotional signals across languages, cultures, and contexts.Models that respond like they’re listening,.
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@OpenAtIntel
open.intel
7 days
It gets better: we didn’t stop at classification. With BUD-E Whisper, we're going beyond transcription to emotion captioning. The model detects emotional tone, vocal bursts (sighs, laughter), and speaker traits from raw speech.
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@OpenAtIntel
open.intel
7 days
Why synthetic data?.No privacy issues.Full demographic control.Massive scalability.More ethical training sets.This is how we generated over 203K facial images and 5K hours of speech with real, measurable emotional intent.
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@OpenAtIntel
open.intel
7 days
And we built models to match. The Empathic Insight-Face model beats Gemini 2.5 Pro and Hume AI on our facial emotion benchmarks. It tracks closely with human annotators across 40 emotions.
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@OpenAtIntel
open.intel
7 days
Emotion is complex. So we didn’t settle for “basic” emotions. EmoNet’s taxonomy includes states like: shame, doubt, pride, fatigue, teasing, even intoxication.It’s built on the Handbook of Emotions and refined with psychologists.
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@OpenAtIntel
open.intel
7 days
We’ve done it differently with EmoNet-Voice:.5,000+ hours of synthetic voice-acted emotion.40 emotion categories.4 languages.Openly licensed.Expert-verified benchmark for real evaluation.In so many vital ways, a major step forward.
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@OpenAtIntel
open.intel
7 days
Let’s start with the problem. Here’s what most speech emotion datasets look like:.Tiny datasets.Coarse labels ("happy," "sad").Narrow speaker demographics.No multilingual support.Often closed license, which makes follow-up and iterative improvements difficult to say the least.
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@OpenAtIntel
open.intel
7 days
It’s called EmoNet: a new open source benchmark + model suite for emotion recognition in speech and facial expressions. This is emotion recognition designed the right way round for once: starting with nuance, not reduction.
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@OpenAtIntel
open.intel
7 days
Emotion isn't binary. It’s messy. Contradictory. Cultural. And we’re finally building AI that can see and hear that.
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@OpenAtIntel
open.intel
8 days
OPEA megaservices don’t do it all—they make it all happen. They run GenAI workflows by coordinating microservices with a blueprint. Modular, efficient and built to scale. Learn more: .
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@OpenAtIntel
open.intel
13 days
What does it take to turn a research idea into a production-ready open source project?. Mona Vij did exactly that with Gramine. At Intel Labs, she leads groundbreaking work in Confidential Computing and trusted execution—from cloud to edge. #OpenSource #MaintainerSpotlight
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@OpenAtIntel
open.intel
14 days
Building #GenAI apps with @OPEAdev?. This article covers orchestration, microservices, and real-time data using Amazon Bedrock and OpenSearch:
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@OpenAtIntel
open.intel
14 days
OPEA megaservices don’t do it all - They make it all happen. They run GenAI workflows by coordinating microservices with a blueprint. Modular, efficient and built to scale. Learn more: .
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@OpenAtIntel
open.intel
15 days
The AI behind Intel® Geti™ is designed to adapt fast. At the core of Geti is a custom model that updates quickly with user feedback. You can train it on your own data, refine it over time, and adjust your setup as conditions change without rebuilding everything from scratch.
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@OpenAtIntel
open.intel
19 days
Why is writing open source documentation still one of the hardest parts of building a thriving project?. In Intel’s 2024 open source community survey, bad or missing documentation was ranked as the #1 challenge for contributors. Too many docs assume too much knowledge. They skip
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@OpenAtIntel
open.intel
20 days
Open source adoption starts with clean, reliable foundations. Kartikey Rameshbhai Parmar makes that happen at @intel, leading Linux OS enablement and Yocto maintenance. #OpenSource #MaintainerSpotlight
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@OpenAtIntel
open.intel
21 days
In this video, @eze_lanza breaks down the differences between @OPEAdev and NVIDIA NIM. If you're deploying GenAI, this quick side-by-side covers what each framework is built for, where they differ, and what to consider based on your stack. More: |
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@OpenAtIntel
open.intel
21 days
Intel at #OSSummit 2025 → Talks on GenAI, edge orchestration & open dev tools. Catch the sessions led by our open source leaders. Visit the booth (G/S16) for hands-on demos & frameworks:.
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