The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

Data Science Weekly - Issue 292

Data Science Weekly Newsletter • 19 implied HN points • 27 Jun 19
🕹 Technology AI
  1. Amazon held its first AI conference showcasing robots and their vision for an efficient future. It was a glimpse into how technology can change everyday tasks.
  2. A new method helped process large DNA sequencing data faster using R and AWK. This approach can help researchers avoid common pitfalls.
  3. Machine learning can improve medical devices, like a better prosthetic hand. This shows how technology can help people lead better lives.

Modeling p(doom) with TrojanGDP

Data Taboo • 5 implied HN points • 22 Sep 23
🕹 Technology AI
  1. There is a lack of mathematical models to assess AI existential risks like p(doom).
  2. The academic community has historically ignored existential risks from AI superintelligence.
  3. The proposed TrojanGDP model aims to estimate the lower bound of AI risk based on factors like GDP contribution and neural Trojan rediscovery.

Data Science Weekly - Issue 291

Data Science Weekly Newsletter • 19 implied HN points • 20 Jun 19
🕹 Technology AI
  1. New AI technology is advancing quickly, enabling robots to be more intelligent and functional. For example, Boston Dynamics has robots that can now actively defend themselves.
  2. Deepfake technology is becoming more sophisticated, allowing a single photo and audio file to create a singing video. This shows how media can be manipulated in exciting and potentially concerning ways.
  3. AI is starting to play roles traditionally held by humans, such as in healthcare. Chatbots are now providing medical advice, which raises questions about their effectiveness compared to real doctors.

Why I Signed the AI Treaty Open Letter

Abstraction • 4 implied HN points • 06 Jan 24
🕹 Technology AI
  1. Balancing concerns about advanced AI with its potential to alleviate suffering is important.
  2. Advanced AI has immense potential to create abundance and shared prosperity if utilized responsibly.
  3. It is crucial to proceed with caution and put safeguards in place to prevent potential devastation from AI.

Data Science Weekly - Issue 290

Data Science Weekly Newsletter • 19 implied HN points • 13 Jun 19
🕹 Technology AI
  1. Facebook has created an AI that can mimic voices, even famous ones like Bill Gates. This technology raises questions about voice authenticity and security.
  2. Machine learning is enabling parents to potentially select traits like intelligence for their children through genetic choices. This could change how we think about heredity.
  3. Deepfake technology is becoming increasingly accessible, allowing users to easily edit videos and create convincing fake content. This poses a challenge for misinformation and trust in media.
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OpenAI vs Self Hosted LLMs: A Cost Analysis

ScaleDown • 5 implied HN points • 19 Sep 23
🕹 Technology AI
  1. OpenAI pricing is token-based, with different costs for input and output tokens, encouraging more detailed prompts for accuracy.
  2. Self-hosted LLMs costs are based on computational resources rather than tokens, with potential for higher costs but no API limits.
  3. Comparing OpenAI and self-hosted LLM costs requires considering utilization rates, where high utilization makes self-hosted more cost-effective.

AI-assisted Ant Colony Optimization with GPT-4 for Solving the Traveling Salesman Problem

Rustic Penn • 2 HN points • 28 Apr 23
🕹 Technology AI
  1. The article explores the synergy between GPT-4 and Ant Colony Optimization for solving the Traveling Salesman Problem.
  2. GPT-4 showcases its potential in guiding and assisting the implementation of the Ant Colony Optimization algorithm.
  3. The combination of AI like GPT-4 with nature-inspired algorithms can lead to innovative and efficient problem-solving solutions.

Data Science Weekly - Issue 288

Data Science Weekly Newsletter • 19 implied HN points • 30 May 19
🕹 Technology AI
  1. Creating general artificial intelligence might be possible through AI-generating algorithms, which could be a better approach than manually piecing together intelligence components.
  2. Generative adversarial networks (GANs) could greatly change the fashion industry by allowing realistic digital models to replace human models in online shopping.
  3. Recent advances in AI technology are enabling more efficient processing on devices, reducing the need for powerful cloud machines and making AI applications more accessible.

LLMs are Level 2 Automation

Maestro's Musings • 7 HN points • 21 Feb 23
🕹 Technology AI
  1. Large Language Models like ChatGPT are currently at Level 2 Automation, not full self-driving.
  2. LLMs have limitations in handling end-to-end scenarios consistently and may require human guidance for accuracy.
  3. Utilizing LLMs effectively involves structuring applications around their limitations and validating outputs before high-stakes actions.

Data Science Weekly - Issue 285

Data Science Weekly Newsletter • 19 implied HN points • 09 May 19
🕹 Technology AI
  1. Machine learning is good at finding patterns in data, but understanding why those patterns exist is still a challenge. This breakthrough could help us understand complex systems better.
  2. Robots can avoid obstacles more effectively with a special type of camera that reduces perception delays. This can help improve how robots navigate through tricky environments.
  3. Stitch Fix uses a game called 'Style Shuffle' to quickly learn about customer preferences. This fun method helps them suggest clothes that people are more likely to buy.

Building Enduring AI Products

Maestro's Musings • 2 HN points • 29 Aug 24
🕹 Technology AI
  1. Large Language Models are powerful but not always the best fit. It's important to choose the right tools for specific tasks instead of relying on one solution for everything.
  2. Integrating AI into workflows makes it more valuable. When AI is part of daily routines, it helps users work better and gives companies a competitive edge.
  3. Focusing on understanding what users really want is key. AI should not just give relevant information, but also grasp the user's intent to be truly helpful.

Data Science Weekly - Issue 281

Data Science Weekly Newsletter • 19 implied HN points • 11 Apr 19
🕹 Technology AI
  1. Unsupervised learning helps computers learn without specific tasks, allowing for more autonomous AI development.
  2. AI is being used to improve farming practices, such as enhancing the flavor of basil.
  3. New AI tools are aiding humanitarian efforts by providing better mapping for disaster response.

What is StarCoder?

Machine Economy Press • 6 implied HN points • 08 May 23
🕹 Technology AI
  1. Hugging Face and ServiceNow released StarCoder, a free code-generating model.
  2. StarCoder is an alternative to other code-generating AI systems like GitHub's Copilot and Google PaLM.
  3. StarCoder is at the intersection of coding and LLMs.

Data Science Weekly - Issue 280

Data Science Weekly Newsletter • 19 implied HN points • 04 Apr 19
🕹 Technology AI
  1. AI is being developed by companies like DeepMind to create powerful technology, raising questions about who controls it. It's an important topic as AI continues to evolve.
  2. Tools like Warby Parker's virtual try-on algorithm show how technology can improve shopping experiences by using real-life simulations, making it easier for customers to make choices.
  3. Innovations in AI, like personalized travel recommendations from TripAdvisor and enhanced speech recognition for Alexa, demonstrate how machine learning can enhance user experiences in daily life.

Data Science Weekly - Issue 278

Data Science Weekly Newsletter • 19 implied HN points • 21 Mar 19
🕹 Technology AI
  1. AI development can lead to positive outcomes, so it's valuable to ask what could go right instead of just focusing on the risks.
  2. New AI techniques, like using GANs, can create exciting content, such as realistic dance videos of athletes.
  3. Reducing the need for labeled data is a key challenge in deep learning, and finding ways to tackle it can enhance model training.

Data Science Weekly - Issue 276

Data Science Weekly Newsletter • 19 implied HN points • 07 Mar 19
🕹 Technology AI
  1. Deep learning can be used to convert imagined words into text using Keras and EEG technology.
  2. There's a new tool called Handtrack.js for quickly creating hand gesture interactions in web apps with TensorFlow.js.
  3. Microsoft Excel now lets you take a picture of a printed spreadsheet and turn it into an editable table, making data handling easier.

AI Spells Doom for Incompetent Hacks

I Might Be Wrong • 6 implied HN points • 21 Apr 23
🕹 Technology AI
  1. AI struggles with creating truly unique and creative content.
  2. AI can excel at generating iterations of existing ideas when the genre is established.
  3. People's fear of AI replacing creative jobs may be overblown; AI likely replaces only those who lack creativity.

Multimodal AI-Edited Supercuts

Multimodal by Bakz T. Future • 1 implied HN point • 24 Feb 25
🕹 Technology AI
  1. Multimodal AI can create supercuts that give quick but immersive experiences of long media. This means you can watch shorter versions of movies or shows without losing the essence of the story.
  2. These AI-generated videos can stitch together scenes and reimagine parts of the original work, providing a fresh way to enjoy familiar content. It's like having a personal editor that knows what you like.
  3. Using technology to make media more accessible for busy people is important. Everyone has different schedules, so having flexible options helps more people enjoy art and storytelling.

How to connect ChatGPT and ElasticSearch?

Machine Economy Press • 6 implied HN points • 20 Apr 23
🕹 Technology AI
  1. Elasticsearch allows for various types of searches like structured, unstructured, geo, and metric.
  2. With Elasticsearch aggregations, you can analyze trends and patterns in large datasets.
  3. Combining ChatGPT with Elasticsearch could lead to innovative, powerful question/answer systems.

AI at the intersection?

Peter’s Substack • 2 implied HN points • 15 Aug 24
🕹 Technology AI
  1. AI technology is improving but mostly in small ways, with major breakthroughs not happening just yet. Many tools are getting faster and cheaper, making them easier to use.
  2. New datasets and improved video generation are exciting developments. Companies like Microsoft and Apple are working on systems that learn from our daily computer use to help automate tasks.
  3. The future of AI holds two possibilities: gradual improvements with existing technology or significant breakthroughs that could change everything. Both paths are possible, so it's important to be ready for either outcome.

If ESG is in the dumps, what will be the new hotness?

Fund Marketer • 3 implied HN points • 27 Mar 24
💰 Finance AI
  1. ESG funds are losing popularity, and some companies are dropping the 'ESG' label from their investment products. This shift reflects growing political pressure and changing market attitudes.
  2. New trends in investing might focus on 'net-zero' goals, emphasizing investments in companies working toward reducing carbon emissions. This could be a fresh way to attract investors concerned about climate change.
  3. Tokenization is on the rise, with firms like BlackRock launching tokenized funds. This means using blockchain technology to manage investments, which could change how investors engage with financial products.

AI Builder Survey

Unsupervised Learning • 2 implied HN points • 21 Aug 24
🕹 Technology AI
  1. OpenAI is very popular among AI builders, but many are experimenting with other models like Claude. A lot of developers are switching models to find better options.
  2. Expect many builders to switch or add new model providers soon. They want better performance, lower costs, and increased security.
  3. Most builders are using techniques like fine-tuning and Retrieval-Augmented Generation to improve their AI models. The focus is shifting more towards fine-tuning as they learn.

GPT is Getting Worse

Donkeyspace • 6 implied HN points • 07 Apr 23
🕹 Technology AI
  1. Earlier versions of GPT had a wild, imaginative energy that newer versions lack.
  2. The recent versions of GPT are calmer, bland, and less creative in their responses.
  3. The evolution of GPT showcases a progression towards professionalism and predictability in its outputs.

AI, Insurtechs and the Coming Wave of US Climate Migration

James Ledbetter's FIN • 5 implied HN points • 23 Jul 23
💰 Finance AI
  1. Insurtech companies are using AI to predict climate risks and help insurance companies price policies accurately.
  2. Climate change is causing more extreme weather events, leading to increased insurance losses and potential migration.
  3. Venture capital funding for insurtechs is on the rise, indicating a growing interest in using technology to address climate risks in the insurance industry.

Data Science Weekly - Issue 273

Data Science Weekly Newsletter • 19 implied HN points • 14 Feb 19
🕹 Technology AI
  1. Curiosity is a key quality for succeeding in data science. It helps professionals think creatively and explore new ideas in their work.
  2. AI can do amazing things, like diagnosing childhood diseases better than some doctors. This shows just how powerful technology can be in healthcare.
  3. Pricing algorithms have become smarter and can now collude to raise prices. This means companies need to be careful about how they implement these systems.

Building Stamina

Tippets by Taps • 6 implied HN points • 02 Apr 23
🕹 Technology AI
  1. Building social stamina after periods of isolation is a process that involves adaptation and new challenges.
  2. The unpredictability and speed of change in post-COVID times require a focus on building resilience and endurance in various aspects of life.
  3. Facing the advancements in AI and the changing landscape of history can be disorienting, requiring psychological and substantive responses.

It's time to Party like it's Pre-AGI! 🎉

Multimodal by Bakz T. Future • 6 implied HN points • 08 Apr 23
🕹 Technology AI
  1. Summer 2023 is a time of heightened AI hype and excitement, with many believing AGI is near.
  2. AGI Fatalism is a mindset where people anticipate AGI leading to catastrophic outcomes, causing them to give up on long-term goals and indulge in pleasure.
  3. It's important to monitor the prevalence of AI Fatalism and encourage adaptability and growth mindset to navigate the societal shifts brought about by AI advancements.

Data Science Weekly - Issue 271

Data Science Weekly Newsletter • 19 implied HN points • 31 Jan 19
🕹 Technology AI
  1. Machine learning projects can be tricky to manage because teams often struggle with setting clear goals and expectations.
  2. Data science can help predict startup valuations, revealing interesting properties and trends in how these valuations are distributed.
  3. New research in AI is making strides in speech reconstruction and facial recognition fairness, but these technologies also raise ethical concerns.

Google SQL Translator API, StackOne €3.3M, Salt Security Developer Portal

The API Changelog • 3 implied HN points • 12 Mar 24
🕹 Technology AI
  1. Google introduced a unified SQL translator API for BigQuery, aimed at enhancing efficiency in translating jobs and supporting various SQL dialects.
  2. StackOne secured €3.3M in seed funding to improve its AI-powered unified API for SaaS enterprises, acknowledging its potential in streamlining SaaS integrations.
  3. Salt Security launched a Developer Portal as a centralized resource to automate API security, focused on improving developer experiences and enabling secure API integrations.

Demystifying GPUs for CPU-centric programmers

The AI Observer • 3 implied HN points • 14 Mar 24
🕹 Technology AI
  1. GPUs are essential for modern compute, especially with the rise of AI workloads like large language models that heavily rely on tensor operations like matrix addition and multiplication.
  2. When working with GPUs, programmers use CUDA to define functions called kernels that can be launched on the GPU. Parallelism is explicitly defined and optimized, unlike in CPUs where loops iterate serially over data sets.
  3. Execution on GPUs differs from CPUs due to the minimal cost of GPU hardware threads, efficient thread scheduling at the hardware layer, and the use of warps to execute parallel instructions. GPUs optimize for high throughput with many hardware threads, while CPUs focus on low latency for individual instructions.

OpenAI EU, Stripe + Bridge, Qualys TotalAppSec

The API Changelog • 1 implied HN point • 11 Feb 25
🕹 Technology AI
  1. OpenAI launched the O3 Mini AI to compete with DeepSeek, aiming to offer top-notch reasoning and coding skills while being free on the ChatGPT platform.
  2. Stripe acquired the stablecoin platform Bridge for $1.1 billion, marking a significant move into the cryptocurrency sector.
  3. Qualys introduced TotalAppSec, an AI-driven tool for managing application risks that helps enhance API safety and web app security.

The other side of the tidal wave

world spirit sock stack • 4 implied HN points • 03 Nov 23
🕹 Technology AI
  1. There's a 10-20% chance of AI causing human extinction in the coming decades.
  2. Even if AI doesn't cause human extinction, life could still go off the rails.
  3. The author worries about the potential disruptions and replacements superhuman AI might bring.

I compared Google Bard with GPT-4 on 10 criteria. The race is not even close | #38

Atomic Learnings • 6 implied HN points • 27 Mar 23
🕹 Technology AI
  1. Google Bard was found to be more creative and engaging, but GPT-4 excelled in accuracy and providing detailed answers.
  2. In a comparison of 10 different criteria, GPT-4 outperformed Google Bard in areas like creativity, handling domain-specific queries, and providing actionable advice.
  3. Bard and GPT-4 both did well in multi-turn conversations, but GPT-4 showed better humor and adaptation to different tones.