The hottest Generative AI Substack posts right now

And their main takeaways
Category
Top Technology Topics
RSS DS+AI Section 23 implied HN points 04 Nov 23
  1. The newsletter covers various topics in Data Science and AI including ethics, research, and practical applications.
  2. Committee activities include calls for new members, updates on AI Safety Summit, and announcements for events like the Christmas social.
  3. The newsletter also highlights significant developments in AI research, such as GenAI, robotics, and Large Language Models.
Infra Weekly Newsletter 18 implied HN points 08 Jan 24
  1. Gentoo adds binary support, a positive move but perhaps a bit late.
  2. Security organizations should ask four key questions when selecting AI-SPM tools to ensure secure AI processes.
  3. Generative AI is set to transform the world in 2024 with advancements in various areas like multimodal models and autonomous agents.
The Product Channel By Sid Saladi 13 implied HN points 10 Mar 24
  1. Cognitive generative AI combines generative models with cognitive computing capabilities, revolutionizing industries like healthcare and creative design.
  2. Generative AI is poised to transform immersive experiences like VR and AR by generating realistic 3D environments in real-time.
  3. Autonomous generative AI agents can make decisions independently, adapting to dynamic environments and revolutionizing industries like customer service and supply chain management.
Get a weekly roundup of the best Substack posts, by hacker news affinity:
The Product Channel By Sid Saladi 13 implied HN points 28 Jan 24
  1. AI product management has various roles like AI Infrastructure PMs, Ranking PMs, Generative AI PMs, Conversational AI PMs, Computer Vision PMs, AI Security PMs, and AI Analytics PMs.
  2. Each type of AI PM role has specific skills and responsibilities like deep knowledge of full AI infrastructure tech stacks for AI Infrastructure PMs, tuning relevance algorithms for Ranking PMs, and incorporating human-in-the-loop feedback loops for Generative AI PMs.
  3. To excel in AI Product Management, it's crucial to understand the landscape, develop relevant skills, and embrace a mindset of continuous learning and adaptation to innovate effectively.
The Digital Anthropologist 19 implied HN points 27 Feb 23
  1. Machines will never think like humans, even with advanced AI technologies.
  2. AI can be helpful for humanity's evolution, but it cannot replicate human consciousness or intelligence.
  3. Culture, critical thinking, and complexity of human interactions are major barriers for AI to truly mimic human behavior.
Perceptions 35 implied HN points 01 Mar 23
  1. ChatGPT and similar frontends have seen fast adoption recently due to their ability to have conversations and answer questions based on vast amounts of written information on the internet.
  2. Large Language Models, like ChatGPT, represent a departure from traditional technology by providing knowledge based on existing information, rather than following specific instructions.
  3. The rise of heuristically thinking machines, such as ChatGPT, shows a shift towards real AI where technology can think and act like humans.
The Product Channel By Sid Saladi 10 implied HN points 07 Jan 24
  1. AI is essential for product managers to stay competitive and create innovative products.
  2. Understanding key AI concepts like machine learning and computer vision is crucial for product managers.
  3. Product managers should adopt offensive and defensive AI strategies to leverage its benefits while mitigating risks.
AI Brews 20 implied HN points 16 Jun 23
  1. Meta AI introduces a new Image Joint Embedding Predictive Architecture model that excels in computer vision tasks and is open-sourced.
  2. McKinsey's report highlights the economic potential of generative AI, estimating it could add trillions annually across various use cases.
  3. EU lawmakers pass regulations for AI systems, requiring review of generative AI like ChatGPT before commercial release and banning real-time facial recognition.
Crypto Good 9 implied HN points 25 Feb 24
  1. Grant Orb is an AI grant writer that can create winning grant proposals in minutes with just a brief project outline, saving up to 95% of your time.
  2. AI is transforming the nonprofit sector by making grant writing more efficient and accessible to organizations of all sizes.
  3. Generative AI technology like Grant Orb can quickly and intelligently create compelling grant proposals, allowing organizations to focus more on their mission and fundraising goals.
More is Different 7 implied HN points 06 Jan 24
  1. Data science jobs may not be as glamorous as they seem, often involving mundane tasks and not much intellectual excitement.
  2. Efforts to create AGI have faced challenges, with ambitious projects like Mindfire encountering skepticism and practical difficulties.
  3. AI in healthcare, such as for radiology, has seen startups struggle and face issues like lack of affordability, deployment challenges, and unpredictability in performance.
AI Brews 17 implied HN points 21 Apr 23
  1. Stability AI released an open-source language model called StableLM trained on a large dataset.
  2. Synthesis AI developed text-to-3D technology to create cinematic-quality digital humans.
  3. Nvidia introduced Video Latent Diffusion Models for high-resolution text-to-video generation.
Marcus on AI 5 HN points 16 Feb 24
  1. The quality of the video produced by OpenAI's latest text-video synthesizer is impressive, almost indistinguishable from reality at a glance.
  2. OpenAI's lack of transparency on training models raises concerns about potential misuse for disinformation and propaganda, especially in upcoming events like the 2024 elections.
  3. Sora's unrealistic physics glitches indicate limitations in generative AI systems like Sora, demonstrating issues in understanding space, time, and causality crucial for building true AGI capabilities.
ScaleDown 5 implied HN points 20 Feb 24
  1. Token-based pricing for LLM applications can be complex as it involves more than just input and output tokens. Consider additional factors like system prompts, context tokens, and evaluation tokens for accurate cost estimation.
  2. Estimating the price of a GenAI chatbot involves considering not only the direct input and output tokens but also context tokens, system prompts, and real-world applications like regeneration and error handling.
  3. When budgeting for GenAI applications, remember to include overheads like evaluation of outputs and guardrails in your cost analysis. These additional requirements can significantly increase the total token costs.
RSS DS+AI Section 11 implied HN points 02 Jun 23
  1. June newsletter focuses on Open Source special, including recent developments in the open source community.
  2. The newsletter highlights activities of the committee, discussions on AI ethics and diversity, and advancements in generative AI.
  3. An in-depth exploration of the open source explosion driven by the development of generative AI, showcasing the surge of open source capabilities and research contributions.
Data Products 5 implied HN points 08 Jan 24
  1. Data quality is crucial for machine learning projects and can have negative impacts on both society and individuals.
  2. Advances in Generative AI highlight the importance of high-quality data and the potential shortage of such data.
  3. Data quality affects the machine learning product development cycle, including ongoing maintenance costs of ML pipelines.
Seeking Tribe 13 implied HN points 05 Mar 23
  1. The internet is changing due to generative AI tools, leading to a potential future where social media is filled with bots.
  2. Niche social media platforms may struggle to compete against big platforms like Twitter, Instagram, and Facebook.
  3. AI tools are advancing, potentially leading to issues like high-fidelity spam, deep fakes, and unrealistic beauty standards.
Computerspeak by Alexandru Voica 1 HN point 05 Apr 24
  1. Advancements in generative AI are transforming the concept of photo albums into interactive synthetic media albums that allow for realistic re-experiencing of memories.
  2. AI-powered interactive photo albums have the potential to revive past loved ones by creating realistic 3D avatars and can also bring back deceased celebrities, bridging generational gaps.
  3. The rise of AI technologies for storytelling raises ethical concerns but offers powerful new ways to preserve and share memories and narratives with future generations.
Res Obscura 3 HN points 16 Feb 24
  1. Long-distance traveling in the premodern world was incredibly dangerous and interesting, taking years from one continent to another.
  2. Generative AI tools like customized GPTs are being used in historical research and as educational tools to simulate historical scenarios.
  3. Comparison between different AI models, like GPT-4, Gemini, and MonadGPT, showed various levels of success in simulating a 17th century doctor's mental models, advice, and speech patterns.
Jakob Nielsen on UX 7 implied HN points 22 Jun 23
  1. AI is introducing the third user-interface paradigm in computing history, shifting from command-based interaction to intent-based outcome specification.
  2. The first UI paradigm was batch processing, where users submitted complete workflows and got results much later, usually with issues in usability.
  3. Command-based interaction, the second UI paradigm, allowed users to assess and modify commands one at a time, with GUIs dominating for about 40 years; AI's intent-based paradigm reverses user control, representing a new era in UI design.
Rod’s Blog 1 HN point 04 Mar 24
  1. Mad Libs game can be a fun and educational tool to practice parts of speech and create hilarious stories with friends.
  2. Proper prompting is crucial for AI systems to generate accurate and relevant responses, understand user intent, and enhance user experience.
  3. Learning how to prompt effectively, especially for security purposes, requires education and can be made fun using games like Mad Libs.
AI Progress Newsletter 7 implied HN points 23 Apr 23
  1. The competition in generative AI is growing as more companies work with large language models.
  2. OpenAI may face challenges in maintaining their lead due to limitations in text data for training larger models.
  3. The future for OpenAI could involve either successfully incorporating videos into models to stay ahead, or facing challenges if they fail to scale up efficiently.
AMQ’s Substack 1 HN point 16 Feb 24
  1. Creativity can be seen as a mix of creation and discovery, especially in the context of art and design.
  2. As technology like Generative AI advances, the line between human creativity and machine generation can become blurred.
  3. Exploring creative processes, whether through AI or imaginative spaces like the Library of Babel, reveals the complex interplay between creating and finding.
Machine Economy Press 3 implied HN points 09 Dec 23
  1. Purple Llama is an umbrella project focusing on developing tools for building responsibly with open AI models.
  2. Purple Llama aims to provide tools and evaluations in areas like cybersecurity and input/output safeguards.
  3. By adopting a purple team concept, Purple Llama emphasizes collaboration to address risks in generative AI development.
Machine Economy Press 3 implied HN points 01 Dec 23
  1. Perplexity AI is working on improving search experience with large language models (LLMs).
  2. Their models offer real-time access to internet data and aim to provide accurate and up-to-date information.
  3. Perplexity's funding and partnerships with major companies like Amazon are crucial for their success and competitiveness in the search engine market.
Chris’s Substack 2 HN points 06 Mar 23
  1. Generative AI technology is advancing creativity by lowering barriers and accelerating the creative process.
  2. Exploring the Explore or Execute productivity framework can help optimize time management by balancing thinking and task execution.
  3. Differentiating between Explore (brainstorming, ideation) and Execute (task completion) modes with practical strategies like setting goals and using timers can enhance productivity.
Machine Economy Press 2 implied HN points 22 Feb 24
  1. Amazon has developed a new, massive text-to-speech model called BASE TTS with emergent abilities, enhancing its natural speech capabilities for AI assistants like Alexa.
  2. The 980 million parameter BASE TTS model is significant for audio and NLP advancements, as it's the largest text-to-speech model created so far.
  3. Text-to-speech and NLP innovations are paving the way for more human-like interactions with voice assistants, marking a shift towards ambient computing.