Snowflake BUILD Keynote: Application Development Using Generative AI
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- čas přidán 18. 12. 2023
- Like electricity, AI is a general-purpose technology with applications in numerous sectors, such as customer support, healthcare, finance, manufacturing, education, and many more. In this talk, Andrew Ng, Founder and CEO of Landing AI, describes some major technology trends:
--Large Language Models (LLMs), beyond being a powerful consumer tool like ChatGPT, is also a powerful developer tool that is enabling many new AI applications to be built quickly and easily.
--Low code development platforms, including ones built on generative AI, are enabling more AI applications to be built not just in the tech sector, but in the “long tail” of AI applications.
--Technology developed and proven out in text processing (LLMs) is also making its way to image data, with the rise of Large Vision Models (LVMs). This is already a key component of how Landing AI provides software that makes computer vision easy.
Many organizations already have massive amounts of data saved on services such as Snowflake. The ease of use of these new AI tools, including specifically, ones that can understand unstructured data such as text (LLMs) and images (LVMs), create many opportunities for developers to quickly build valuable new applications that take advantage of this data.
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thx you very much for all your quality educational work!!!!!!!!!!!!!
Amazing!
🎯 Key Takeaways for quick navigation:
00:13 🌐 *AI is the new electricity, transforming industries; focus on identifying and building possibilities enabled by AI.*
01:08 🧠 *Two crucial AI tools are supervised learning (mapping input to output) and generative AI (creating high-quality media like text, images, and audio).*
03:49 📈 *The last decade saw large-scale supervised learning; the current decade is marked by the rise of generative AI, enhancing AI applications.*
07:48 🚀 *Prompt-based AI shortens development cycles, allowing rapid prototyping and deployment of AI applications in minutes or days.*
12:59 🛠️ *Low-code tools, prompting, and data-centric AI make it easier for developers to customize and build their own AI systems, addressing the long-tail problem.*
23:35 🖼️ *Large vision models and domain-specific foundation models are emerging trends, adapting to unique image datasets for improved applications.*
25:49 🌐 *Training domain-specific foundation models on proprietary datasets in your data warehouse can unleash large vision models tailored to specific applications.*
26:18 🚀 *The computer vision field is experiencing an explosion of applications across diverse industries, showcasing creative uses in agriculture, e-commerce, healthcare, manufacturing, and more.*
27:26 💡 *Encouragement to explore and extract value from images and videos within Snowflake's data storage, leveraging the Landing AI platform and SDK for building applications.*
27:52 🤝 *Acknowledgment of the respect for the Snowflake community's work and an invitation to engage with the Landing AI platform.*
Made with HARPA AI
Nice tool! Thanks!
Great presentation
Glad you liked it
Wow the legendary Andrew Ng partnering with Snowflake!
AI: The New Electricity Powering Application Development (Snowflake BUILD Keynote)
00:13 AI is the new electricity, transforming every industry like electricity did 100 years ago.
00:39 Key AI tools: supervised learning (maps inputs to outputs) and generative AI (creates high-quality media).
01:08 Supervised learning: spam filtering, online advertising, self-driving cars, manufacturing defect inspection, sentiment analysis (e.g., restaurant reviews).
02:14 Workflow for supervised learning: data set (inputs & labels), train AI model, deploy model (e.g., cloud service).
02:55 Trend: large-scale supervised learning - bigger models & data = better performance.
03:49 This decade: generative AI's rise - text generation, code completion, image creation.
04:17 How generative AI works: uses supervised learning to predict next word in a sequence (e.g., training on massive text datasets).
05:40 Prompting revolutionizes AI application development: build software applications faster (hours/days vs. months) with prompts instead of traditional workflows.
06:22 Traditional workflow: data labeling (1 month), model training (3 months), deployment (3 months).
06:36 Prompt-based workflow: specify prompt (minutes/hours), deploy to production (hours/days).
06:48 This faster cycle enables rapid prototyping, idea testing, and building more AI applications.
Key Takeaways:
AI is transforming industries like the new electricity.
Supervised learning and generative AI are key tools.
Large-scale models and data improve AI performance.
Prompting revolutionizes AI application development with faster workflows.
I hope this concise summary, emphasizing the video's key points and leveraging timestamps for structure, helps you recall and understand the main takeaways.
AI's Future: Prompting, Low-code Tools, and the Long Tail (Snowflake BUILD Keynote)
07:18 Building AI apps faster with prompts in Jupyter notebooks (e.g., sentiment classifier with "positive/negative" output).
07:46 Prompt-based workflow revolutionizes development: build apps in minutes/days vs. months (traditional).
08:12 Free online courses on deeplearning.ai to learn and build your own AI applications.
08:39 Projected market value of AI technologies: supervised learning dominates now (~$100B/year for Google alone), generative AI rapidly growing.
09:22 Long tail of smaller AI projects ($5M) presents huge potential but requires customization due to lack of one-size-fits-all models.
10:04 The "long tail" problem: valuable AI projects follow a decreasing value curve, with billion-dollar giants like online ads at the head and niche applications like pizza defect detection at the tail.
11:50 Low-code tools and prompting empower developers to build custom AI for these niche applications.
12:05 Key technologies for custom AI: prompting (text & visual), data-centric AI (focusing on data collection and preparation).
12:59 Data-centric AI emphasizes acquiring the right data to train successful AI systems ("code + data").
13:43 Practical approach: focus on robust code implementation and high-quality data acquisition for efficient AI development.
14:10 Moving beyond text prompting: exploring visual prompting and other advancements in generative AI.
Key Takeaways:
Prompting and low-code tools unlock faster, easier AI application development.
The "long tail" of niche AI projects offers vast potential for customization.
Data-centric AI and acquiring the right data are crucial for successful AI systems.
Generative AI is rapidly evolving, with exciting possibilities beyond text prompting.
I hope this concise summary, highlighting key points with timestamps, helps you grasp the video's main ideas and their future implications.
AI's Next Wave: Visual Prompting and Beyond (Snowflake BUILD Keynote)
14:24 The future of AI lies in computer vision and image processing. Build text-based AI apps today, but prepare for the visual revolution.
14:38 Demo: Building a webcam app to monitor Zoom attentiveness using supervised learning (image classification).
15:20 Landing Lens platform simplifies AI development: upload images, label data, train models with a click.
16:50 This ease and speed enable rapid prototyping and deployment of AI applications.
17:18 Apply this workflow to your Snowflake image data or easily acquired images for value extraction.
19:00 Beyond supervised learning: visual prompting with generative AI for even faster development.
19:14 Example: crack detection in images with minimal pixel-level labeling and Transformer Network generation.
20:23 Prompting a generative AI model with labeled pixels, similar to text prompting in language models.
20:49 Biologists use visual prompting to train AI for cell colony detection on microscope slides.
21:18 Iterative visual conversation: refine AI's understanding by providing additional labels and feedback.
22:01 The future of AI: building applications in minutes with visual prompting, similar to text prompting's impact.
Key Takeaways:
Computer vision and visual prompting are the next frontiers of AI development.
Landing Lens platform democratizes AI creation with its user-friendly interface.
Generative AI with visual prompting accelerates development and expands possibilities.
AI is rapidly evolving, blurring the lines between imagination and creation.
I hope this concise summary, emphasizing key points with timestamps, helps you grasp the exciting advancements in AI and their potential to revolutionize various fields.
The Future of AI: Vision Revolution, Domain-Specific Models, and Beyond (Snowflake BUILD Keynote)
22:15 Text-based AI revolutionized language processing (GPT-3, etc.). Visual prompting with Transformers is poised to do the same for computer vision.
22:55 Vision transformers are rapidly evolving, building on the foundation of text transformer advancements.
23:22 The "vision revolution" is a few years behind text, but breakthroughs in image processing are promising.
23:35 Large vision models and domain-specific foundation models are key to unlocking the potential of diverse image data.
23:48 Unlike text, internet images (happy people, cats) often differ from company-specific data (semiconductor wafers, microscope slides).
24:42 Training domain-specific foundation models on proprietary data (e.g., semiconductor images) yields superior performance for specialized tasks (defect detection).
25:23 This approach is applicable to various fields like life sciences (cell images for pathology) and healthcare (X-rays for disease diagnosis).
25:49 We're in the early stages of an explosion of computer vision applications across diverse industries.
26:18 Landing AI highlights the creativity of developers in building applications like crop health monitoring, e-commerce, medical image analysis, and more.
27:26 The speaker encourages exploring image and video data stored in Snowflake for potential value extraction and application development.
27:40 Landing AI platform and SDK are readily available for building and integrating custom AI applications.
28:06 AI development thrives on the data infrastructure provided by Snowflake and similar platforms.
28:19 The speaker expresses enthusiasm for future collaborations and exploring AI's possibilities further.
Key Takeaways:
Visual prompting and domain-specific AI models are revolutionizing computer vision.
Proprietary image data holds immense potential for specialized AI applications.
Diverse industries are rapidly adopting and innovating with AI-powered vision solutions.
Landing AI platform and similar tools empower developers to build custom AI applications with ease.
The future of AI promises even more exciting advancements and transformative applications.
I hope this concise summary, emphasizing key points with timest
Thanks
Ai in games rts will be so hard in future
Andrew is still brilliant, why to start selling himself in sponsored talks?
To make money 🧐
So he can eat
0:35 व
money is money. being brilliant doesn't stop you from wanting money.