Browse Lessons

Real-world AI demands live data, not static data corpus. Fine-tuning sensitive data leads to leakage

Natural program integrates deductive verification into the chain of thought, self-verified by LLM.

Demos optimize costs, energy, performance, and privacy in on-device AI with full-stack optimization

AI Trends 2024: Computer Vision with Naila Murray - 665

Prediction of shift in LLMs: Embedding desiderata in training to avoid post hoc interventions.

The greatest leverage towards generative AI challenges means defining specific use cases and metrics

Markus' approach: not quantization method but a solution to eliminate activation quantization issues

Are Vector DBs the Future Data Platform for AI? with Ed Anuff - 664

Quantizing Transformers by Helping Attention Heads Do Nothing with Markus Nagel - 663

The power of generative models is open-endedness, but this also poses challenges for responsible AI

Success lies in listening, engaging, adapting to evolving needs and building sticky, useful products

Responsible AI in the Generative Era with Michael Kearns - 662

Making learning enjoyable and using play as motivation sparks increased engagement and interest

PartyRock sparks generative AI intuition through playful, no-code app building—unleashing creativity

Edutainment for AI and AWS PartyRock with Mike Miller - 661

Coactive transforms workflows, shifting from TLS to LST, revolutionizing image & video data handling

Building at Coactive is like building a car: Model-agnostic for easy upgrades and future-proof ready

Data, Systems and ML for Visual Understanding with Cody Coleman - 660

Explore diverse tool collaboration for enhanced LLM solutions, usability, and dev-friendly solutions

Retrieval patterns allows the model to act as a ‘problem-solving brain’, yielding smarter solutions.

Patterns and Middleware for LLM Applications with Kyle Roche - 659

LLM cost management is a concern. Off-the-shelf models offer budgeting, alerting, and monitoring

AI should ease burdens on users. Diverse data is key for fairness, inclusivity, and accessibility.

Prem highlights “invention rich areas” in AI and invention challenges as these technologies evolve

Boost AI by working with academia to define targeted datasets and foster open synthetic data culture

AI Access and Inclusivity as a Technical Challenge with Prem Natarajan - 658

Upgrading hardware isn't always the fix. Strategic design is key to overcoming latency challenges

Ensure startup relevance by innovating beyond one feature and aiming for long-term value and impact

Building LLM-Based Applications with Azure OpenAI with Jay Emery - 657

Visual Generative AI Ecosystem Challenges with Richard Zhang - 656

Engineers use simulation to tackle bias and adversarial examples, and enhance robust model solutions

Applying MLOps techniques enhances speed and consistency in deploying edge and embedded AI systems

Deploying Edge and Embedded AI Systems with Heather Gorr - 655

Investing in robust tools ⚙️ is valuable for managing risk and enabling contribution among teams

Building a unicorn team: ✅ Diverse skills ✅ Open communication ✅ Continuous learning

The AI moratorium letter signals existential risks to the public and urges caution in AI development

Yoshua calls for enhanced regulations, investments, and countermeasures for AI safety and defense

AI Sentience, Agency and Catastrophic Risk with Yoshua Bengio - 654

Delivering AI Systems in Highly Regulated Environments with Miriam Friedel - 653

AI concerns demand traceability. Resource allocation sparks values divide in present & future models

The main challenges for multilingual models: balancing languages and dealing with poor data quality.

Turn problems to checklists and restructure from low to high-level judgments to avoid hallucinations

Anthropomorphism in terminology is inevitable but it’s important to clarify these are just metaphors

Prompting pretrained models is subtractive, unveiling the model's behavior and text predictions

Mental Models for Advanced ChatGPT Prompting with Riley Goodside - 652

Finding global talent and open collaboration are keys to establishing unique and meaningful research

Multilingual LLMs and the Values Divide in AI with Sara Hooker - 651

Evaluating AI's general performance & finding models for unrestricted prompting remains a challenge