How you can go about hiring your VP of Engineering?
A nicely laid out framework here (from @Shopify 's VP of Engineering)
Great share, @fnthawar https://t.co/SI9LZKCUru #mlopsworld2021
Semantic similarity is not the same thing as answer retrieval.
Lean on embeddings as the default for every use case and you get systems that sound convincing while returning weak, incomplete, or confidently incorrect answers.
David vonThenen, @NetApp .
Every software company claims to be becoming an AI company. Most are re-running the wrong playbook: treating AI like an infrastructure migration instead of a shift in how products are designed, shipped, and operated.
Alet Blanken, @Workday . TMLS 2026.
The default assumption in AI security is that encryption costs performance. Fully Homomorphic Encryption, especially.
The talk analyzes trade-offs between encryption overhead and latency, using open-source FHE and model optimizations.
Tyson Macaulay, @01quantuminc
A robot that can recall what it did last week needs memory across three dimensions: spatial, descriptive, and visual.
That is the architecture behind experience recall for temporal question answering in agentic robots.
@stevewaslander , @UofT
Agent vulnerability is primarily architectural, not a model alignment problem.
Fixing the model without addressing orchestration logic leaves the most exploitable attack surface untouched.
Naga Sujitha Vummaneni, @Ripple
TMLS 2026 → https://t.co/ZeMnODpBeq
$26/month infrastructure. 200+ languages served. A core team of three.
That's the Multilingual Climate Chatbot, a production RAG system, open-source and easy to adopt.
Luis Ticas + Helena Yu, Sprout Climate
Real data can be a legitimate option for pre-training tabular foundation models - despite being underutilized in favour of synthetic data.
It captures complex signals critical for downstream generalization.
Anthony Caterini @Layer6AI is exploring that here at TMLS 2026
Evals in production: the #1 constraint our committee flagged this year.
Korede Adegboye is presenting his framework at TMLS 2026: automated dataset curation, failure-mode detection, and uncertainty-aware decisioning.
→ See All Speakers: https://t.co/F0oeCcK9cZ
Vino Sangaralingam is automating and productionizing an NLP-based process with a GenAI component in regulated finance and payments, where ROI and measurement need to be built into the pipeline from day one.
She’s on the MLOps World Steering Committee.
Ten years of Canadian AI practitioners in one room, and once again, that room is at CIBC.
Proud to have them back as Platinum Sponsor and host venue for our 10th annual summit.
TMLS 2026 · June 16–19 · Toronto, CA
→ https://t.co/6uCXCS55td
One person with the right AI tools can go from idea to working product in days.
TMLS and FGF Brands are putting that to the test at Toronto Tech Week. 5-day agentic hackathon, any stack, demo to judges on Friday.
May 25–29, Toronto, CA
Vinothini Sangaralingam is productionizing NLP with a GenAI component in regulated finance and payments, where governance and auditability aren't optional.
She's on the TMLS 2026 Steering Committee.
TMLS 2026 · June 16–19 · Toronto, CA
→ Learn more: https://t.co/ia0qouq55O
He's joining the MLOps World I GenAI Summit 2026 Steering Committee.
If this is your problem space, this is the room built for it.
→ Learn more: https://t.co/F2BRHhRoXB
Dippu Singh is building AI systems that combine high-precision models with geospatial data to detect security anomalies across live feeds, focused on architectures that are scalable, trustworthy, and safe for enterprise decision-making.
Dippu Singh is building real-time AI systems that detect security anomalies across live geospatial data feeds, where the architecture has to be trustworthy enough to act on automatically.
He's on the TMLS 2026 Steering Committee.
TMLS 2026 · June 16–19 · Toronto, CA
Teams are getting evals green and still not getting systems into production.
If you've had to make that call, the MLOps World committee wants to hear from you.
→ Submit your session: https://t.co/iP2BJrqo6s
Austin, TX · Nov 17–18