3rd Global AI & Emerging Technologies Conference

Welcome to the Global AI & Emerging Technologies Conference!

Join us for a cutting-edge event where experts from around the world will discuss the latest trends and innovations in artificial intelligence (AI) and other emerging technologies. The conference will be held in person at Toronto Metropolitan University, Hall B92, providing a unique opportunity to network and learn from industry leaders.

Don't miss out on this chance to gain valuable insights and stay ahead of the curve in the ever-evolving world of technology. Whether you're a seasoned professional or just starting out in the field, there's something for everyone at the Global AI & Emerging Technologies Conference. See you there!

INVITATION LETTER is provided upon registration for the event

Contact: [email protected]

“Responsible Intelligence at Scale: From Research to Real-World Impact.”Focus on deploying AI and emerging tech (edge computing, robotics, quantum-adjacent methods, XR) that are safe, equitable, and commercially viable.

1. Knowledge Exchange: Latest applied AI breakthroughs and scalable architectures.
2. Skills Building: Hands-on labs in MLOps, LLM alignment, RAG systems, and secure deployment.
3. Partnerships: Matchmaking among startups, enterprises, universities, and investors.
4. Policy & Trust: Practical governance toolkits for privacy, bias mitigation, and safety.
5. Commercialization: Live accelerator-style pitch reviews and procurement roundtables.

• CTOs, CIOs, Heads of AI/DS, product leaders
• ML engineers, data scientists, platform & DevOps teams
• Health, finance, manufacturing, gov/public sector innovation leads
• Researchers, PhD candidates, postdocs
• Investors, accelerators, corporate venture units
• Policy makers, standards bodies, legal & compliance professionals

• Single-day, high-density program with hands-on labs and exec roundtables.
• Cross-sector case studies (health, finance, climate, smart cities).
• Practical governance—templates and checklists you can use the next day.
• Direct access to partners (universities, labs, incubators, integrators).
• Certification options to validate new skills (see below).

• Visa-supporting documentation (official invitation letters with agenda & role).
• Global standards alignment (ISO/IEC AI mgmt references, model cards, data sheets).
• North American market access: investor office hours & partner matchmaking.
• Credentialed learning with Certificates of Completion and CPE/CPD hours.

• Academic: Toronto Metropolitan University (host), Vector Institute (AI), University+College labs
• Industry: Cloud providers, chip makers (CPU/GPU/accelerators), MLOps platforms, cybersecurity vendors
• Public/Standards: Municipal/Provincial innovation units, standards bodies, privacy commissioners
• Ecosystem: Startup accelerators, industry associations (health, finance, manufacturing)

(Confirm and brand these based on actual agreements.)

Capacity: Hall B92 (theatre) + adjacent breakout rooms (2–3) for labsRoom Setup:

• Keynote room: theatre; stage with confidence monitor, dual projectors, 4 wireless mics + 2 handhelds
• Labs: classroom pods (5–6 per table), robust Wi-Fi, power strips, whiteboardsA/V & Tech: 4K projection, HDMI/USB-C hookups, clickers, recording (optional), hybrid streaming-readyWi-Fi: Dedicated SSID for presenters + separate attendee SSID; minimum 1 Gbps down / 200 Mbps upCatering: coffee/pastries morning, boxed lunch, two snack breaks, speaker green roomAccessibility: step-free access, reserved seating, CART/ASL on request, alt-text in slides templateSustainability: digital agenda, reusable signage, locally sourced catering, bottle-fill stationsSafety: on-site first aid, emergency contacts, clear evacuation routesRegistration Desk Hours: 07:45–17:30

• Certificate in Responsible AI Implementation (Level 1) – 6 CPE/CPD hours
• • Awarded upon attending the Governance Track + Lab 2 + completing a short assessment (online).
• MLOps Practitioner Micro-Credential – 6 CPE/CPD hours
• • Awarded upon completing Lab 1 + Lab 3 + passing an applied quiz.(Digital badges issued within 7 business days.)

Prereqs for labs: Laptop with admin rights; Python 3.10+ and Docker installed; optional GPU access via provided cloud credits.

1. Lab 1: Production LLMs & RAG Systems (2 hrs)
2. • Build a retrieval-augmented generation pipeline with vector search, evals, and guardrails.
   • Takeaway: repo template + deployment checklist.
3. Lab 2: Responsible AI & Governance Toolkit (1.5 hrs)
4. • Bias measurement, privacy risk triage, model card creation, incident response tabletop.
   • Takeaway: governance templates + DPIA starter.
5. Lab 3: MLOps & Cost Optimization (1.5 hrs)
6. • CI/CD for models, model registry, monitoring (drift, hallucination rates), autoscaling.
   • Takeaway: reference pipeline + cost dashboard workbook.
7. Exec Roundtable: AI Strategy & ROI (invite-only, 1 hr)
8. • KPIs, build vs. buy, roadmap patterns, vendor diligence.

All times local (Toronto, EDT).

07:45–08:45 Registration, Coffee, Networking08:45–09:00 Welcome & Land Acknowledgment (TMU representative)09:00–09:35 Opening Keynote: Responsible Intelligence at Scale09:35–10:10 Keynote Fireside: AI Safety Meets Business Outcomes10:10–10:30 Networking Break

10:30–12:00 Parallel Tracks

• Track A (Technology):
• • Vector Databases in Practice (30)
  • Efficient Fine-Tuning (LoRA/QLoRA) (30)
  • Edge AI & On-Device Models (30)
• Track B (Sectors):
• • Healthcare AI with Privacy by Design (30)
  • Finance: GenAI for Risk & Compliance (30)
  • Manufacturing: Vision + Robotics (30)

12:00–13:00 Lunch & Poster Session (student/industry demos)

13:00–14:30 Labs Block 1

• Lab 1 (RAG systems) – Room L1
• Governance Mini-Workshop (policy leads) – Room G1

14:30–14:45 Coffee Break

14:45–16:15 Labs Block 2

• Lab 2 (Responsible AI) – Room L2
• Executive Roundtable – Boardroom

16:15–17:00 Case Study Lightning Talks (5 × 9 mins)17:00–17:45 Pitch Showcase: Startups & Research-to-Market17:45–18:00 Closing Remarks & Certificate Instructions18:15–19:30 Optional Networking Reception (near campus)

• Vector DBs in Practice: Patterns for hybrid search, chunking, evals, and latency SLAs.
• Efficient Fine-Tuning: Parameter-efficient strategies, safety guardrails, eval frameworks.
• Edge AI: Model compression, quantization, and privacy-respecting inference.
• Healthcare AI: De-identification, clinical LLMs, validation protocols.
• Finance GenAI: Audit trails, prompt logging, model risk governance.
• Vision & Robotics: Synthetic data, safety interlocks, and throughput gains.

Tiers & Benefits (examples):

• Title Partner (1): Logo on stage, keynote slot, 20×20 demo space, 10 passes.
• Platinum (3): Track naming, panel seat, 10×20 booth, 6 passes.
• Gold (6): Workshop co-host, 10×10 booth, 4 passes.
• Startup/Ecosystem: Pod desk in startup alley, 2 passes.All tiers include lead retrieval, opt-in attendee contact list, and content syndication rights (per consent).

• Startup Alley: curated 15 startups (health, fintech, robotics, tooling).
• Innovation Posters: students/industry R&D with QR-linked abstracts.
• Hands-On Pods: sandbox stations for live model testing.

• Pre-event interest survey → algorithmic session & meeting suggestions.
• Investor office hours (sign-up required).
• Sector tables at lunch (health/finance/manufacturing/public sector).
• Birds-of-a-Feather breakouts during coffee windows.

“Responsible Intelligence at Scale: From Research to Real-World Impact.”Focus on deploying AI and emerging tech (edge computing, robotics, quantum-adjacent methods, XR) that are safe, equitable, and commercially viable.

1. Knowledge Exchange: Latest applied AI breakthroughs and scalable architectures.
2. Skills Building: Hands-on labs in MLOps, LLM alignment, RAG systems, and secure deployment.
3. Partnerships: Matchmaking among startups, enterprises, universities, and investors.
4. Policy & Trust: Practical governance toolkits for privacy, bias mitigation, and safety.
5. Commercialization: Live accelerator-style pitch reviews and procurement roundtables.

• CTOs, CIOs, Heads of AI/DS, product leaders
• ML engineers, data scientists, platform & DevOps teams
• Health, finance, manufacturing, gov/public sector innovation leads
• Researchers, PhD candidates, postdocs
• Investors, accelerators, corporate venture units
• Policy makers, standards bodies, legal & compliance professionals

• Single-day, high-density program with hands-on labs and exec roundtables.
• Cross-sector case studies (health, finance, climate, smart cities).
• Practical governance—templates and checklists you can use the next day.
• Direct access to partners (universities, labs, incubators, integrators).
• Certification options to validate new skills (see below).

• Visa-supporting documentation (official invitation letters with agenda & role).
• Global standards alignment (ISO/IEC AI mgmt references, model cards, data sheets).
• North American market access: investor office hours & partner matchmaking.
• Credentialed learning with Certificates of Completion and CPE/CPD hours.

• Academic: Toronto Metropolitan University (host), Vector Institute (AI), University+College labs
• Industry: Cloud providers, chip makers (CPU/GPU/accelerators), MLOps platforms, cybersecurity vendors
• Public/Standards: Municipal/Provincial innovation units, standards bodies, privacy commissioners
• Ecosystem: Startup accelerators, industry associations (health, finance, manufacturing)

(Confirm and brand these based on actual agreements.)

Capacity: Hall B92 (theatre) + adjacent breakout rooms (2–3) for labsRoom Setup:

• Keynote room: theatre; stage with confidence monitor, dual projectors, 4 wireless mics + 2 handhelds
• Labs: classroom pods (5–6 per table), robust Wi-Fi, power strips, whiteboardsA/V & Tech: 4K projection, HDMI/USB-C hookups, clickers, recording (optional), hybrid streaming-readyWi-Fi: Dedicated SSID for presenters + separate attendee SSID; minimum 1 Gbps down / 200 Mbps upCatering: coffee/pastries morning, boxed lunch, two snack breaks, speaker green roomAccessibility: step-free access, reserved seating, CART/ASL on request, alt-text in slides templateSustainability: digital agenda, reusable signage, locally sourced catering, bottle-fill stationsSafety: on-site first aid, emergency contacts, clear evacuation routesRegistration Desk Hours: 07:45–17:30

• Certificate in Responsible AI Implementation (Level 1) – 6 CPE/CPD hours
• • Awarded upon attending the Governance Track + Lab 2 + completing a short assessment (online).
• MLOps Practitioner Micro-Credential – 6 CPE/CPD hours
• • Awarded upon completing Lab 1 + Lab 3 + passing an applied quiz.(Digital badges issued within 7 business days.)

Prereqs for labs: Laptop with admin rights; Python 3.10+ and Docker installed; optional GPU access via provided cloud credits.

1. Lab 1: Production LLMs & RAG Systems (2 hrs)
2. • Build a retrieval-augmented generation pipeline with vector search, evals, and guardrails.
   • Takeaway: repo template + deployment checklist.
3. Lab 2: Responsible AI & Governance Toolkit (1.5 hrs)
4. • Bias measurement, privacy risk triage, model card creation, incident response tabletop.
   • Takeaway: governance templates + DPIA starter.
5. Lab 3: MLOps & Cost Optimization (1.5 hrs)
6. • CI/CD for models, model registry, monitoring (drift, hallucination rates), autoscaling.
   • Takeaway: reference pipeline + cost dashboard workbook.
7. Exec Roundtable: AI Strategy & ROI (invite-only, 1 hr)
8. • KPIs, build vs. buy, roadmap patterns, vendor diligence.

All times local (Toronto, EDT).

07:45–08:45 Registration, Coffee, Networking08:45–09:00 Welcome & Land Acknowledgment (TMU representative)09:00–09:35 Opening Keynote: Responsible Intelligence at Scale09:35–10:10 Keynote Fireside: AI Safety Meets Business Outcomes10:10–10:30 Networking Break

10:30–12:00 Parallel Tracks

• Track A (Technology):
• • Vector Databases in Practice (30)
  • Efficient Fine-Tuning (LoRA/QLoRA) (30)
  • Edge AI & On-Device Models (30)
• Track B (Sectors):
• • Healthcare AI with Privacy by Design (30)
  • Finance: GenAI for Risk & Compliance (30)
  • Manufacturing: Vision + Robotics (30)

12:00–13:00 Lunch & Poster Session (student/industry demos)

13:00–14:30 Labs Block 1

• Lab 1 (RAG systems) – Room L1
• Governance Mini-Workshop (policy leads) – Room G1

14:30–14:45 Coffee Break

14:45–16:15 Labs Block 2

• Lab 2 (Responsible AI) – Room L2
• Executive Roundtable – Boardroom

16:15–17:00 Case Study Lightning Talks (5 × 9 mins)17:00–17:45 Pitch Showcase: Startups & Research-to-Market17:45–18:00 Closing Remarks & Certificate Instructions18:15–19:30 Optional Networking Reception (near campus)

• Vector DBs in Practice: Patterns for hybrid search, chunking, evals, and latency SLAs.
• Efficient Fine-Tuning: Parameter-efficient strategies, safety guardrails, eval frameworks.
• Edge AI: Model compression, quantization, and privacy-respecting inference.
• Healthcare AI: De-identification, clinical LLMs, validation protocols.
• Finance GenAI: Audit trails, prompt logging, model risk governance.
• Vision & Robotics: Synthetic data, safety interlocks, and throughput gains.

Tiers & Benefits (examples):

• Title Partner (1): Logo on stage, keynote slot, 20×20 demo space, 10 passes.
• Platinum (3): Track naming, panel seat, 10×20 booth, 6 passes.
• Gold (6): Workshop co-host, 10×10 booth, 4 passes.
• Startup/Ecosystem: Pod desk in startup alley, 2 passes.All tiers include lead retrieval, opt-in attendee contact list, and content syndication rights (per consent).

• Startup Alley: curated 15 startups (health, fintech, robotics, tooling).
• Innovation Posters: students/industry R&D with QR-linked abstracts.
• Hands-On Pods: sandbox stations for live model testing.

• Pre-event interest survey → algorithmic session & meeting suggestions.
• Investor office hours (sign-up required).
• Sector tables at lunch (health/finance/manufacturing/public sector).
• Birds-of-a-Feather breakouts during coffee windows.

• Venue & A/V: stage, recording, Wi-Fi upgrades
• Catering: coffee breaks, lunch, reception
• Staffing: registration, speaker ops, A/V techs, volunteers
• Marketing: ads, design, printing minimal
• Insurance & Contingency: 10–15% buffer
• Revenue: registrations, sponsorships, exhibitor fees, grants

• Privacy: clear data collection notice; session tracking opt-outs
• Ethics: AI demo safety policy; no sensitive PII processing on-site
• Health & Safety: first-aid on-site; incident response lead; emergency comms plan

Tagline: “Build smarter systems—safely, responsibly, and at scale.”Channels: partner newsletters, LinkedIn campaigns, academic lists, incubators.Assets: speaker social kit, sponsor kit, email sequences (T-8, T-4, T-1 weeks), press note.

Tickets are available for individual attendees, corporate groups, and students. Don’t miss your chance to be a part of the Global AI & Emerging Technologies Conference . Register now to secure your spot and take your career or business to the next level!

Terms & Conditions :

• Please note that all registration fees are non-refundable, non-negotiable, and non-transferable.
• Please make your own arrangements for visa (if applicable), accommodation, meals, and transportation during the conference.
• After completing the registration and verifying your successful payment, a regular invitation letter will be sent within 2 business days.

NB-Contact for invitation letter : [email protected]

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