DALL·E is a 12-billion parameter version of GPT-3 trained to generate images from text descriptions, using a dataset of text–image pairs
#ai
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https://openai.com/blog/dall-e/

#papers #ai
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https://www.datasciencecentral.com/profiles/blogs/ii2020

Worlds First Audio Earrings
#ai #artificialintelligence
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https://www.instagram.com/p/CMOVCBTAUPQ/?igshid=wu464niw7rcg

#ai #artificialintelligence
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https://www.technologyreview.com/2020/10/16/1010566/ai-machine-learning-with-tiny-data/amp/?__twitter_impression=true

#ai
@kdnuggets @datasciencechats
https://ai.facebook.com/blog/ai-can-now-emulate-text-style-in-images-in-one-shot-using-just-a-single-word

Researchers from Facebook AI, berkeley_ai, and SCSatCMU have developed #AI that can enable a legged robot to adapt in fractions of a second to changing conditions in the real world.
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https://www.instagram.com/p/CRJBcVfDbRY

Future of Interior Design
#virtualreality #ai
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https://www.instagram.com/p/CRWcaCDjH7Q/?utm_medium=copy_link

Intro to AI course materials are available by University Of California - Berkeley:

1. Lecture slides and videos
2. Homework assignments with solutions
3. Section Handouts
4. Specs for the Pacman Projects
5. Source files and PDFs of past Berkeley CS188 exams
#freecourse #AI #artificialintelligence
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LINK: https://bit.ly/31sEHke
Join @coursenuggets for more

#healthcare #AI #machinelearning
https://news.mit.edu/2022/deploying-machine-learning-improve-mental-health-rosalind-picard-0126

AI Week - Session recordings including keynotes sessions now freely available. 3 Day virtual event participations from Intel/PayPal etc.
#training #AI
@kdnuggets @datasciencechats @coursenuggets
https://aiweek2022.b2b-wizard.com/expo/agenda

AI tool detects CVD on cardiac MRI in 20 seconds with high precision
#ai #healthcare

@kdnuggets @datasciencechats
https://www.healthimaging.com/topics/medical-imaging/magnetic-resonance-imaging/ai-detects-cvd-cardiac-mri-20-seconds

The #DeepLearning Course by top #AI researcher Yann Lecun at NYU CDS is Now Fully Online & Accessible to All.
#freecourse #university #deeplearning
@coursenuggets @kdnuggets
Details:
https://nyudatascience.medium.com/yann-lecuns-deep-learning-course-at-cds-is-now-fully-online-accessible-to-all-787ddc8bf0af


Lectures:
https://atcold.github.io/pytorch-Deep-Learning/

https://aws.amazon.com/events/aws-innovate/apj/aiml-data/
#AWS #ai #ml
@kdnuggets @datasciencechats

https://ai.facebook.com/blog/segment-anything-foundation-model-image-segmentation/
#ai #imagesegmentation
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Curated list of Artificial Intelligence courses, books 📚,video lectures and papers 📝

https://github.com/owainlewis/awesome-artificial-intelligence

@coursenuggets @kdnuggets @datasciencenuggets
#courses #ai

Marketing strategy and AI-Free Webinar from Google

In this session you will learn:

How is AI changing the marketing landscape and what are the opportunities for marketers

AI-powered marketing tools you can try

Supercharging your digital marketing strategy

https://bit.ly/googleaimarketing

#ai #freecourse #marketing
@kdnuggets @datasciencechats @coursenuggets

AI Python for beginners Free course for limited period by Andrew Ng
#ai #python
Join @coursenuggets for more
@kdnuggets @datasciencechats

https://www.deeplearning.ai/short-courses/ai-python-for-beginners/

Building LLMs - Stanford Course
#ai #generativeai #llm

https://www.youtube.com/watch?v=9vM4p9NN0Ts

@kdnuggets @datasciencechats

00:10 Building Large Language Models overview
02:21 Focus on data evaluation and systems in industry over architecture
06:25 Auto regressive language models predict the next word in a sentence.
08:26 Tokenizing text is crucial for language models
12:38 Training a large language model involves using a large corpus of text.
14:49 Tokenization process considerations
18:40 Tokenization improvement in GPT 4 for code understanding
20:31 Perplexity measures model hesitation between tokens
24:18 Comparing outputs and model prompting
26:15 Evaluation of language models can yield different results
30:15 Challenges in training large language models
32:06 Challenges in building large language models
35:57 Collecting real-world data is crucial for large language models
37:53 Challenges in building large language models
41:38 Scaling laws predict performance improvement with more data and larger models
43:33 Relationship between data, parameters, and compute
47:21 Importance of scaling laws in model performance
49:12 Quality of data matters more than architecture and losses in scaling laws
52:54 Inference for large language models is very expensive
54:54 Training large language models is costly
59:12 Post training aligns language models for AI assistant use
1:01:05 Supervised fine-tuning for large language models
1:04:50 Leveraging large language models for data generation and synthesis
1:06:49 Balancing data generation and human input for effective learning
1:10:23 Limitations of human abilities in generating large language models
1:12:12 Training language models to maximize human preference instead of cloning human behaviors.
1:16:06 Training reward model using softmax logits for human preferences.
1:18:02 Modeling optimization and challenges in large language models (LLMs)
1:21:49 Reinforcement learning models and potential benefits
1:23:44 Challenges with using humans for data annotation
1:27:21 LLMs are cost-effective and have better agreement with humans than humans themselves
1:29:12 Perplexity is not calibrated for large language models
1:33:00 Variance in performance of GPT-4 based on prompt specificity
1:34:51 Pre-training data plays a vital role in model initialization
1:38:32 Utilize GPUs efficiently with matrix multiplication
1:40:21 Utilizing 16 bits for faster training in deep learning
1:44:08 Building Large Language Models from scratch

https://cloud.google.com/blog/products/application-development/firebase-studio-lets-you-build-full-stack-ai-apps-with-gemini
#ai

@kdnuggets @datasciencechats

🚀 Popular YouTube Channels to Learn AI & ML 🤖📚
Whether you’re a beginner or going deep into research, these channels are gold for AI/ML learning 👇
1️⃣ Andrej Karpathy – Learn deep learning straight from a legend
👉 Watch here
2️⃣ Sebastian Raschka – Clear explanations on ML, PyTorch & research
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3️⃣ sentdex – Hands-on Python, ML & practical coding
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4️⃣ StatQuest with Josh Starmer – ML & stats made ridiculously simple
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5️⃣ Jeremy Howard – Practical deep learning & fast. ai insights
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6️⃣ Krish Naik – End-to-end AI, ML & career-focused content
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7️⃣ CampusX – Structured data science & ML learning paths
👉 Watch here
8️⃣ 3Blue1Brown – Math intuition behind ML like never before
👉 Watch here
9️⃣ MIT OpenCourseWare – World-class AI & ML courses for free
👉 Watch here
🔟 Stanford Online – Learn AI from the pioneers shaping the field
👉 Watch here
Follow @coursenuggets for more.
Our other channels @kdnuggets @datasciencechats

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#AI #MachineLearning #DeepLearning #DataScience #LearningResources