AI for Developers_ Empowering Innovation & Creativity — SwitchCon

AI for Developers_ Empowering Innovation & Creativity — SwitchCon

Transcript

1. AI in the Digital Age: Empowering Innovation & Creativity Olayinka Peter Oluwafemi, Google Developer Expert, Machine Learning October 2023
2. $whoami • ML Google Developer Expert • Senior ML @ Credit Direct • ❤ TensorFlow, anime & peanut butter • Coordinates 󰗓 coffeewithpeter.com
3. AI in the Digital Age: Empowering Innovation & Creativity
4. The Impact of AI across several sectors Finance Technology Health
5. The Impact of AI across several sectors Finance Technology Health • KYC • Fraud detection • Risk assessment • Market Data Analysis • Personalised financial advice
6. The Impact of AI across several sectors Finance Technology Health • KYC • Fraud detection • Risk assessment • Market Data Analysis • Personalised financial advice • Medical imaging • Predictive analytics • Drug discovery • Personalized treatment plans
7. The Impact of AI across several sectors Finance Technology Health • Self-driving cars • Natural language processing (LLMs, etc) • Image recognition • So many more • KYC • Fraud detection • Risk assessment • Market Data Analysis • Personalised financial advice • Medical imaging • Predictive analytics • Drug discovery • Personalized treatment plans
8. Significant transformative contributions
9. Significant transformative contributions Economic growth $15.7 trillion by 2030
10. Significant transformative contributions Economic growth $15.7 trillion by 2030 Manufacturing 20% reduction in unplanned downtime 10-20% improved throughput
11. Significant transformative contributions Economic growth $15.7 trillion by 2030 Manufacturing 20% reduction in unplanned downtime 10-20% improved throughput Job creation 12 million new jobs by 2025
12. Significant transformative contributions Economic growth $15.7 trillion by 2030 Manufacturing 20% reduction in unplanned downtime 10-20% improved throughput Agriculture AI-led precision agriculture improved crop yield by 4-5% Job creation 12 million new jobs by 2025
13. AI tools and platforms
14. AI tools and platforms 1. Machine Learning Frameworks
15. AI tools and platforms 2. AI Development Platforms - Google Cloud Vertex AI - Microsoft Azure AI - IBM Watson - OpenAI - …
16. AI tools and platforms 2. AI Development Platforms - Google Cloud Vertex AI - Microsoft Azure AI - IBM Watson - OpenAI - … Offer pre-built AI services, APIs, and development environments for tasks such as: • Natural language processing • Computer vision • Speech recognition • Generative AI
17. how much of the power of generative AI do we already have in our palms?
18. Google Cloud Vertex AI Overview Unified development and deployment platform for data science, machine learning, and generative AI
19. Google Cloud Generative AI Empower enterprises to innovate faster with enterprise-ready generative AI APIs | SDK | Libraries AI Platform AI Notebooks Experiment | Train | Deploy Prompt | Tune | Distill | Extend ML Ops | RAI & Eval Tooling Google Cloud Infrastructure (GPU/TPU) | Google Data Cloud Model Garden Build Your Own Gen AI powered Agents AI Solutions Doc AI Contact Center AI Translation Hub Risk AI User Interfaces: Voice | UI Widgets | Multimodal | … Generative AI Studio Search & Conversation Data Connectors Extensions Orchestrate Grounding Enterprise Readiness NTK Google Models PaLM, Codey, Imagen, Chirp, Embeddings… Open Source Models LLaMA 2, Falcon, Stable Diffusion… Partner Models Claude 2,… Broad Ecosystem of Partners Search Retrieve | Summarize | Generate Conversation Answer | Generate | Transact … Model Garden Vertex AI Data Governance Data Privacy Responsible AI Security & Compliance
20. Vertex AI Pre-Trained Models Vision Language Conversation Vision Video Intelligence AutoML Vision AutoML Video Intelligence Translation Natural Language AutoML Natural Language AutoML Translation Speech-to-Text Dialogflow Text-to-Speech Best in class tools allowing customers to leverage Google’s leadership in AI to solve common problems Structured data Fleet Routing API AutoML Tables Vertex AI Forecast Time Series Insights API TabNet Speaker ID
21. Model Garden Generative AI Studio Open Source Models Task Specific AutoML and APIs Foundation Models Tuning Adaptive Layers Prompt Design Data Science Workbench (Colab Enterprise & Workbench Instances) Experiment Train Deploy MLOps ML Platform Vertex AI Platform provides data science, ML, and Gen AI practitioners with tools to customize and build
22. Vertex AI Model Garden 01 One stop shop 02 Use Foundation Models directly 03 Tune Foundation Models 04 Customize popular open source models 05 API access to task-specific solutions One place to launch various enterprise user journeys
23. 01 A simple UI for interacting with models 02 Tune models with your own data 03 Use models in production 04 Multiple modalities Generative AI Studio Simple UI for interfacing, experimenting, and tuning models
24. Vertex AI areas of investment 1 Unified Data & AI platform for all users to accelerate time to value 2 End-to-End MLOps to efficiently and responsibly manage and govern AI 3 Open and Scalable AI Infrastructure to flexibly and successfully deploy AI State-of-the-Art AI to drive innovation and improve customer outcomes 4
25. SaaS Applications IoT Devices Social Media Corporate and 3rd Systems Geospatial Decision Making App Development SaaS Applications Exception Management Operational Intelligence Data Monetization Data engineers Clean, useful data Data scientists Models that work Developers Intelligent apps Data analysts Query and analyze ML engineers Integrated intelligence Consumers Value Business users Insights Everywhere E-Commerce Google’s Data Cloud ANY USER ANY DATA ANY INNOVATION ANY WORKLOAD DATA ENGINEERING DATA ANALYSIS MODEL DEVELOPMENT ML ENGINEERING INSIGHTS ACTIVATION Dataproc Vertex AI Vertex AI Vertex AI BigQuery Cloud Composer Looker Cloud Run Vertex AI Pipelines Dataflow An Integrated Data ⇒ Value Journey
26. What will you build?
27. Some learning resources Online Courses and Tutorials: • Coursera • edX • Udacity • Google's Machine Learning Crash Course Forums and Communities: • Stack Overflow • Reddit - Machine Learning
28. Books: • "Deep Learning" - by Ian Goodfellow, Yoshua Bengio, and Aaron Courville: A comprehensive introduction to deep learning. • "Python Machine Learning" - by Sebastian Raschka and Vahid Mirjalili: A book that covers practical machine learning with Python. • "Artificial Intelligence: A Modern Approach" - by Stuart Russell and Peter Norvig: A foundational textbook in AI. Some learning resources
29. Questions?
30. thank you. Olayinka Peter Oluwafemi he/him @olayinkapeter_