ML. The Pioneer Way. #MachineLearning #MLOps
🇺🇸 / 🇫🇮
Joined October 2016
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LLM evaluation should not live in personal notebooks.
When results stay isolated, knowledge stays isolated.
Serious deployment requires shared visibility, reproducibility and structured comparison.
That is how experimentation becomes engineering.
How to avoid shipping the wrong LLM:
1. Use your own dataset
2. Label categories and complexity
3. Track model and parameters
4. Aggregate per category
5. Compare side by side
The goal is not the highest number.
It is understanding behavior.
#ValohaiLLM #LLMEvals
Structured LLM evaluation in 3 lines of Python.
Post every run with model, dataset and metrics.
Make results searchable and comparable.
Aggregate by category.
Structure beats memory.
valohai.com/llm/
If you cannot reproduce your LLM comparison next week, you do not have a comparison.
You have a memory.
#ValohaiLLM valohai.com/llm/
Your +2% LLM improvement is probably noise.
Small datasets
Mixed prompt types
No category splits
No reproducible tracking.
Averages hide more than they reveal.
If you cannot reproduce the comparison next week, it is not a real evaluation.
#ValohaiLLM
3 days to #OVHcloudPartnerNetworkSummit25!
Stop by the @valohaiai booth → Automate MLOps at European scale 🇪🇺
#AI #MLOps #OVHcloudSummit25
Secure. Compliant. Scalable.
Automate MLOps at European scale with Valohai on @OVHcloud ☁️
📍 Nov 20, Paris
#OVHcloudPartnerNetworkSummit25
ovh.to/RLz2SHA
🇪🇺 Valohai + @OVHcloud = faster, cheaper, compliant #AI
Meet us at #OVHcloudPartnerNetworkSummit25 → Nov 20, Paris
Automate MLOps at European scale 🌩️
🔗 ovh.to/RLz2SHA
"We need more GPUs."
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2 weeks in 🚀
Valohai + Oracle = SageMaker-like MLOps for OCI.
Enterprise-ready, compliant, and already making impact in regulated industries.
valohai.com/blog/valohai-on-…
AlphaFold is revolutionary. But without the right workflow, it’s slow, expensive, and frustrating.
✅ Run at scale
✅ Control GPU usage
✅ Speed up research
🔗 Learn how: hubs.ly/Q03KXQzJ0
#AlphaFold #GenAI #MLOps
Running AlphaFold is easy.
Running it efficiently at scale? That’s the real science. 🔬
👉 Learn how: hubs.ly/Q03KXQzJ0
#AlphaFold #GenAI #MLOps #MLEfficiency
Biologist: “Can I test this sequence in AlphaFold?”
Engineer: “Sure, but let’s resize the cluster first.”
Ops: “And reconfigure access.”
IT: “And approve it.”
👉 Research shouldn’t move at bureaucratic speed.
🔗 Read more: hubs.ly/Q03KXQzJ0
#AlphaFold #GenAI
No GPU/CPU metering.
Valohai = per-user license.
Your infra bill = yours.
Our value = automation, reproducibility & governance.
#CloudComputing #DataScience #MachineLearning #InfrastructureAsCode #DevOps #MLOps #AIResearch
GPU queues: ⏳
Unoptimized runs: 💸
Blocked experiments: 😩
AlphaFold is powerful — but without the right workflow, it drains time & budgets.
👉 See how to fix it: hubs.ly/Q03KXQzJ0
#AlphaFold #GenAi #MLEfficiency #CostOptimization
Biologist: “Can I just test this sequence in AlphaFold?”
Engineer: “Sure, once we resize the GPU cluster”
Ops: “And open the right ports”
IT: “And approve the request”
👉 Discovery shouldn’t be a bureaucratic relay race.
🔗 Blog: hubs.ly/Q03KXQzJ0
#AlphaFold #GenAI
