Vector Institute transforms cutting-edge artificial intelligence research into practical solutions. AI-generated content will be disclosed. FR: @InstitutVecteur
Toronto
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Our social, economic, and political systems patch vulnerabilities at a human pace. Artificial intelligence operates at computer speed.
On October 22, security technologist Bruce Schneier will outline why this speed disparity matters. In Conversations in Computing: Hacking AI, he will explore how AI models are discovering and exploiting loopholes in human rule systems, from tax codes to financial markets.
Join Vector, @UofTCompSci, and @TorontoSRI for this in-person discussion:
📅 Thursday, Oct. 22 at 5:00 - 7:00 p.m
📍 Schwartz Reisman Innovation Campus, Toronto
ℹ️ Free admission, registration required.
Reserve your seat: na3.hubs.ly/y0GtsL0
We’re proud to welcome the @TownofCaledon as our first municipal partner. 🤝
Together, we’re bridging world-class AI research with civic reality, testing practical use cases, and building internal capacity to ensure any new technology deployed is safe, responsible, and focused on better outcomes for residents.
Learn more: na3.hubs.ly/y0Gq-W0
Vector Institute retweeted
1/🧵New Research on LLM-Driven Discovery!
LLMs are increasingly used to discover new algorithms, theorems, and drugs by iteratively optimizing an objective inside a "harness."
Our finding: How you initialize a discovery harness matters a lot more than you might expect.
Are you applying for AI master’s programs in Ontario? Here’s how to put yourself in the running for an entrance scholarship with serious industry access.
For the 2027–28 academic year, the Vector Scholarship in AI (VSAI) increases to a $21,000 entrance award. Recipients also step straight into Canada’s most active AI ecosystem.
Here’s what VSAI recipients gain: 👇
Ready to plan your master’s pathway?
Explore Ontario’s 30 Vector-recognized programs and learn more about how the VSAI can open doors to your future today: na3.hubs.ly/y0FK8M0
When AI systems search complex enterprise documents, standard retrieval methods often pull isolated snippets instead of connecting the facts; standard vector similarity search breaks down when retrieval-augmented generation pipelines require multi-hop reasoning.
Our AI Engineering team developed an alternative Entity-Based Knowledge Graph RAG architecture that increases retrieval accuracy by up to 54% on complex queries.
Continue reading to learn more, or go straight to the full analysis: vectorinstitute.ai/enhancing…
The results show clear advantages for structured knowledge. On complex multi-hop queries, retrieval accuracy increased from 40 per cent to 55 per cent using GPT-4o.
Smaller, cost-effective models like GPT-4o-mini jumped from 36 to 56% accuracy, all while adding only 0.05 seconds of latency. Providing structural context allows these smaller models to match the performance of larger models.
Giving models structured context allows them to deliver high accuracy without heavy compute costs.
Vector's Ali Kore and Amrit Krishnan detail the complete extraction pipeline, evaluation methodology, and open-source code in our latest technical post: vectorinstitute.ai/enhancing…
How does cognitive science help us build better AI?
At our 2026 AI Summit and Career Fair, Vector Faculty Member @KelseyRAllen broke down how human cognition exposes the limits of state-of-the-art systems, and how we can fix them.
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As AI systems improve, they also begin to shape human cognition, often leading to overreliance. The feedback loop is constant.
As Allen noted: "How do we measure human and machine intelligence as they start to reshape each other?"
Want to learn more? Catch the full presentation on our youtube channel: youtube.com/watch?v=7JYwx4fz…
