The hottest Generative models Substack posts right now

And their main takeaways
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Top Technology Topics

Don’t Ride This Bike! Generative AI’s persistent trouble with compositionality and parts

Marcus on AI • 3952 implied HN points • 08 Dec 24
🕹 Technology AI Machine Learning Image Processing Natural Language Generative models
  1. Generative AI struggles with understanding complex relationships between objects in images. It sometimes produces physically impossible results or gets details wrong when asked to create images from text.
  2. Recent improvements in AI models, like DALL-E3, show only slight progress in handling specifications related to parts of objects. It can still mislabel parts or fail to follow more complex requests.
  3. AI systems need to improve their ability to check and confirm that generated images match the prompts given by users. This may require new technologies for better understanding between language and visuals.

Import AI 364: Robot scaling laws; human-level LLM forecasting; and Claude 3

Import AI • 519 implied HN points • 11 Mar 24
🕹 Technology AI Robots Generative models Biology
  1. Scaling laws are transforming the world of robotics - more data, bigger context windows, and more parameters in models lead to significant improvements quickly.
  2. Advancements in AI forecasting show that language models can match human capabilities in predicting binary outcomes, suggesting a future of accurate forecasting by AI systems.
  3. New datasets like Panda-70M for video captioning and models like Evo for biological predictions are pushing the boundaries of AI and demonstrating the power of generative models in various domains.

You should build your own eval tools, pretty much always

The Hypernatural Blog • 16 HN points • 09 Sep 24
🕹 Technology AI Tools Video Production Model Evaluation Generative models User Experience
  1. Building your own evaluation tools early can greatly improve your product's quality. It's easier than you think and pays off in the long run.
  2. For complex systems, off-the-shelf tools may not fit well. Creating custom tools helps you better understand and improve system performance.
  3. Using real-world examples in your evaluations leads to better outcomes. Make sure to test how changes affect actual user experiences.

Import AI 358: The US Government’s biggest AI training run; hacking LLMs by hacking GPUs; chickens versus transformers

Import AI • 319 implied HN points • 29 Jan 24
🕹 Technology AI Cybersecurity Multimodal models Generative models
  1. Hackers can exploit GPU vulnerabilities to read data from LLM sessions, highlighting security risks in AI infrastructures.
  2. AI will enhance cyberattacks and empower malicious actors, posing a significant threat to cybersecurity by increasing efficiency and sophistication of attacks.
  3. The US government conducted a substantial AI training run but lags behind private industry, showcasing the need for advancements in supercomputing capabilities for large-scale AI models.

Import AI 343: Humanlike AI; LLaMa 2 protests; the NSA's new AI center

Import AI • 439 implied HN points • 09 Oct 23
🕹 Technology AI Robotics Data Security Generative models
  1. Google DeepMind and 33 labs created a large dataset for training robots, showing that using heterogeneous data and high-capacity models improves robot performance.
  2. Protests have begun against Facebook for releasing AI models that can be easily modified, raising concerns about AI safety becoming a political issue.
  3. Generative image models are displaying human-like qualities in tasks, like shape bias and understanding perceptual illusions, suggesting a convergence between AI systems and humans.
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Import AI 334: Better distillation; the UK's AI taskforce; money and AI

Import AI • 399 implied HN points • 10 Jul 23
🕹 Technology AI Research Generative models Funding AI Applications
  1. DeepMind developed Generalized Knowledge Distillation to make large models cheaper and more portable without losing performance.
  2. The UK's £100 million Foundation Model Taskforce aims to shape the future of safe AI and will host a global summit on AI.
  3. Significant financial investments in AI, like Databricks acquiring MosaicML for $1.3 billion, indicate growing strategic importance of AI in various sectors.

This is Why We Can't Have Nice Things

The Weasel Speaks • 157 implied HN points • 27 May 23
🕹 Technology AI Automation Software Development Generative models
  1. Agile has three main views in the industry: it doesn't work, it's taking away jobs, it accelerates value to customers.
  2. Technological disruptions often make people feel like their jobs are in jeopardy.
  3. AI stirs opinions: it's criticized for not working, it's accused of taking jobs, yet it can accelerate learning and revolutionize work.

Modular Deep Learning

MLOps Newsletter • 78 implied HN points • 27 Jan 24
🕹 Technology Deep Learning Generative models Classes
  1. Modular Deep Learning proposes splitting models into smaller, independent modules for specific subtasks.
  2. Modularity in AI development can lead to collaborative and efficient ecosystem and democratize AI development.
  3. PyTorch 2.0 introduces performance gains such as faster inference and training speeds, autotuning, quantization, and improved memory management.

AI (Automated Interpolation)

Logging the World • 139 implied HN points • 26 Apr 23
🕹 Technology AI Machine Learning Artificial Intelligence Generative models Language Models
  1. Models are good at interpolating known data but struggle with extrapolating beyond that, which can lead to significant errors.
  2. AI models excel at interpolation tasks, creating mashups of existing styles based on training data, but may struggle to generate genuinely new, groundbreaking creations.
  3. Great works of art often come from pushing boundaries and exploring new styles, something that AI models, bound by training data, may find challenging.

Edge 374: Some Technical Details we Learned About OpenAI's Sora

TheSequence • 140 implied HN points • 29 Feb 24
🕹 Technology AI Generative models Video Engineering
  1. OpenAI's Sora is a groundbreaking text-to-video model that can create high-quality videos up to a minute long.
  2. The release of Sora has caused a lot of excitement and discussion in the generative AI community and media outlets.
  3. While OpenAI has not revealed extensive technical details about Sora, the model includes some clever engineering optimizations.

Language is a SimCity

Cybernetic Forests • 59 implied HN points • 02 Jul 23
🔬 Science Language Statistics AI Generative models Neural Networks
  1. Language can be seen as a dynamic city, shaped by collective contributions that form its intricate structure.
  2. Generative AI models, like GPT4, rely on statistics and random selection to produce text, often betraying a lack of true understanding.
  3. Human communication involves a choice between shallow, statistically-driven speech, like that of machines, and deeper, intent-driven speech that seeks to convey personal truths.

Embed Retrieve Win

Gradient Flow • 99 implied HN points • 29 Sep 22
🕹 Technology Machine Learning Data Infrastructure Generative models NLP AI Applications
  1. Embeddings are low-dimensional spaces that make AI applications faster and cheaper while maintaining quality.
  2. Vector databases are designed for vector embeddings and are becoming essential for modern search engines and recommendation systems.
  3. Generative models like diffusion models are gaining attention in the research community and offer great opportunities for exploration and innovative projects.

Practico-inertia

Internal exile • 29 implied HN points • 01 Mar 24
🕹 Technology AI Generative models Search Engines Language Models
  1. Generative models like Google's Gemini can create controversial outputs, raising questions about the accuracy and societal impact of AI-generated content.
  2. Users of generative models sometimes mistakenly perceive the AI output as objective knowledge, when it is actually a reflection of biases and prompts.
  3. The use of generative models shifts power dynamics and raises concerns about the control of reality and information by technology companies.

Update #69: Gemini Overcompensates for Bias and Missing Details in Sora

The Gradient • 20 implied HN points • 27 Feb 24
🕹 Technology AI Ethics Generative models AI safety Funding
  1. Gemini AI tool faced backlash for overcompensating for bias by depicting historical figures inaccurately and refusing to generate images of White individuals, highlighting the challenges of addressing bias in AI models.
  2. Google's recent stumble with its Gemini AI tool sparked controversy over racial representation, emphasizing the importance of transparency and data curation to avoid perpetuating biases in AI systems.
  3. OpenAI's Sora video generation model raised concerns about ethical implications, lack of training data transparency, and potential impact on various industries like filmmaking, indicating the need for regulation and responsible deployment of AI technologies.

Emu Video Edit , General game-playing AI agent, fully autonomous AI software engineer, DeepSeek-VL, Robotics Foundation Model, and more

AI Brews • 17 implied HN points • 15 Mar 24
🕹 Technology AI Generative models Robotics Natural Language Processing
  1. DeepSeek-VL is a new vision-language model for real-world applications with competitive performance.
  2. Cognition Labs introduces Devin, the first fully autonomous AI software engineer, capable of learning, building, and deploying apps.
  3. The European Parliament approved the Artificial Intelligence Act, which bans certain AI applications including biometric categorization and emotion recognition in specific contexts.

Mistral Large, vocal expressive avatar videos, Generative virtual worlds, Reliable text rendering and Magic Prompt, DJ Mode, AI-powered film making and more

AI Brews • 17 implied HN points • 01 Mar 24
🕹 Technology AI Virtual Worlds Generative models
  1. Mistral introduced new models like Mistral Large with top-tier reasoning abilities and Mistral Small optimized for latency and cost.
  2. Alibaba introduced EMO, a framework that generates expressive vocal avatar videos from a single reference image and vocal audio.
  3. Ideogram launched Ideogram 1.0, a text-to-image model focused on state-of-the-art text rendering and a Magic Prompt feature to assist with prompting.

Update #47: AI Index Report Highlights and Text-to-3D

The Gradient • 20 implied HN points • 11 Apr 23
🕹 Technology AI Research Models Publications Generative models
  1. The AI Index Report highlights industry leading in AI research over academia, new models reaching performance saturation, and a rise in AI misuse.
  2. Publication trends show an increase in journal articles over conference papers, industry surpassing academia in impactful research, and increased industry hiring over academia.
  3. Advancements in text-to-3D models leverage text-to-2D models, showing progress in generating 3D data from text descriptions.

Truth and consequences

Internal exile • 5 HN points • 08 Mar 24
🕹 Technology AI Social media Disinformation Generative models Fact-checking
  1. Generated images on food delivery apps are often perceived as placeholders to fulfill basic requirements, not meant to deceive or enhance the customer's experience
  2. Generative images symbolize a power shift where technology companies dictate realities that must be accepted, regardless of quality or accuracy, aligning users with this new authority
  3. Concerns over fake images highlight the complexities of truth and reality perception, emphasizing the need to navigate between obviousness, evidence, and asceticism in seeking truth

Update #48: Generative AI in Law & Art and Promptable Vision Models

The Gradient • 11 implied HN points • 25 Apr 23
🕹 Technology AI Generative models Neural Networks Research Ethical Implications
  1. Generative AI is transforming fields like Law and Art, raising ethical and legal questions about ownership and bias.
  2. Recent models allow users to specify vision tasks through flexible prompts, enabling diverse applications in image segmentation and visual tasks.
  3. Advances in promptable vision models and generative AI pose challenges and opportunities, from disrupting professions to potential ethical and legal implications.

LLMs and Generative AI don't deal with concepts

Top Carbon Chauvinist • 1 HN point • 13 Apr 24
🕹 Technology AI Machine Learning Generative models Computing Patterns
  1. LLMs and generative AI focus on patterns, not real concepts. They generate outputs based on learned data but don’t actually understand what those outputs mean.
  2. When asked to create an image, like an ouroboros, generative AI often misses the mark. It replicates the look without truly grasping the idea behind it.
  3. To get the desired result, people often have to give very detailed prompts, which means the AI is more about matching shapes than understanding or creating an actual concept.

Occasional Exponential AI Grab Bag

Gradient Ascendant • 9 implied HN points • 13 Feb 23
🕹 Technology AI Machine Learning Generative models Language Models Artificial Intelligence
  1. AI advancements are moving at an incredibly fast pace, with new developments happening almost every week.
  2. The current AI growth resembles a Cambrian explosion, but remember that exponential growth eventually slows down.
  3. Language models are now able to self-teach and use external tools, showcasing impressive advancements in AI capabilities.

LLM Data Sales: A Market for Lemons?

Magis • 1 HN point • 14 Feb 24
🕹 Technology AI Models Generative models Model Training
  1. Selling data for training generative models is challenging due to factors like lack of marginal temporal value, irrevocability, and difficulties in downstream governance.
  2. Traditional data sales rely on the value of marginal data points that become outdated, while data for training generative models depends more on volume and history.
  3. Potential solutions for selling data to model trainers include royalty models, approximating dataset value computationally, and maintaining neutral computational sandboxes for model use.

How Far Are We From Being Able to Generate Whatever 3D Objects On the Fly?

I'll Keep This Short • 0 implied HN points • 17 Jul 23
🕹 Technology AI 3D Modeling Generative models Neural Networks Large Language Models
  1. AI-generated 3D objects are still far from being created instantly in real 3D
  2. Shap-E improves upon previous models by generating 3D objects using Neural Radiance Fields
  3. Although new technologies show promise, limitations like resource-intensive processes and lack of fine details still exist

AI is contributing to a rise in energy demand; your child’s next toy could be powered by ChatGPT; AI will be a powerful tool for the future of work; will AI ever outsmart us?

Computerspeak by Alexandru Voica • 0 implied HN points • 26 Jan 24
🕹 Technology AI Renewable Energy Generative models Energy Efficiency AI Applications
  1. AI is contributing to a rise in energy demand, leading to challenges like increased electricity consumption and the unexpected need to delay closing coal-fired power plants in some areas.
  2. Investments in renewable energy are on the rise, with more funds now going into clean energy projects compared to traditional fossil fuels, showcasing a positive shift towards sustainability.
  3. Researchers are exploring spiking neural networks inspired by the brain's efficiency to reduce the energy footprint of AI, potentially opening doors to new applications like long-range search and rescue, prosthetics, and edge computing.

Generative A-Eye #3 - 18th Sept,2024

Martin’s Newsletter • 0 implied HN points • 18 Sep 24
🕹 Technology AI Image Synthesis Computer Vision Deep Learning Generative models
  1. Gaussian Splatting is seen as a strong alternative to traditional deepfake methods, especially for smaller projects like commercials and music videos. Some experts believe it may not be ready for big Hollywood movies yet, but it shows promise.
  2. OmniGen is a new image generation model that simplifies tasks like image editing and can perform many functions without needing extra systems. However, its legality is questionable due to data sources.
  3. A new method for detecting deepfakes uses a phone's vibration to reveal inconsistencies in fake videos, providing a practical solution to identifying deepfakes in real time.

Amazon doubles down on Anthropic

The PhilaVerse • 0 implied HN points • 28 Nov 24
🕹 Technology AI Cloud Computing Investment Partnerships Generative models
  1. Amazon is investing an extra $4 billion in Anthropic, making their total investment $8 billion. This shows how serious Amazon is about developing AI technology.
  2. Anthropic will now use Amazon's cloud services as their main platform for training AI models. This partnership aims to make AI models more powerful and secure.
  3. Anthropic's AI models, like Claude 3.5, are popular in various industries for different tasks, including customer service and drug discovery. Many companies are already using these advanced tools.

Designing Better Evaluations of Generative Models

Tom’s Substack • 0 implied HN points • 11 Nov 23
🕹 Technology AI/ML Evaluation Generative models Red-Teaming
  1. Evaluation of models should focus on selecting the best performing model, giving confidence in AI outputs, identifying safety and ethical issues, and providing actionable insights for improvement.
  2. Standard evaluation approaches face challenges like broad performance metrics, data leakage from benchmarks, and lack of contextual understanding.
  3. To improve evaluations, embrace human-centered evaluation methods and red-teaming to understand user perceptions, uncover vulnerabilities, and ensure models are safe and effective.

Mixture of Experts LLM shows real promise in healthcare; the future of AI is multimodal and multilingual; why AI is having a 1995 moment; a closer look at diffusion transformers;

Computerspeak by Alexandru Voica • 0 implied HN points • 01 Mar 24
🕹 Technology Artificial Intelligence Healthcare Multimodal models Generative models
  1. Generative AI models like BiMediX, PALO, and GLaMM are advancing healthcare, language models, and image understanding in multilingual settings.
  2. Innovative models like MobilLlama aim to make AI more accessible by running on affordable hardware and being optimized for mobile devices.
  3. AI applications in various industries, such as journalism, construction, and e-commerce, are enhancing safety, optimizing workflows, and transforming user experiences.