The hottest Technology Substack posts right now

And their main takeaways
Category
Top Technology Topics

Data Science Weekly - Issue 130

Data Science Weekly Newsletter • 19 implied HN points • 19 May 16
🕹 Technology Data science Machine Learning Programming Statistics Analytics
  1. Transcribing long-term rental ads can provide valuable insights into housing price trends. This type of data collection helps inform discussions on affordable housing.
  2. Data natives, or people who grew up using technology, expect smart systems that adapt to their preferences seamlessly. This shift is changing how we interact with data and technology.
  3. Power analysis is important for scientists planning experiments. It helps them understand if an experiment will be effective and what data they need to collect.

Peak Data

East Wind • 2 HN points • 25 Oct 23
🕹 Technology AI Data Quality ML models Training Data
  1. The quality and percentage of human-generated data on the internet may have reached a peak, affecting the efficacy of future AI models.
  2. Models may face challenges with outdated training data and lack of relevant information for solving newer problems.
  3. Potential solutions include leveraging RAG models, proactive data contribution by platform vendors, and maintaining incentives for human contributions on user-generated content platforms.

Five years of progress in GPTs

Artificial Fintelligence • 3 HN points • 29 Mar 23
🕹 Technology Language Models Research Innovation Optimization
  1. Focus on the evolution of GPT models over the past five years, highlighting key differences between them.
  2. Explore the significant impact of large models, dataset sizes, and training strategies on language model performance.
  3. Chinchilla and LLaMa papers reveal insights about the optimal model sizes, dataset sizes, and computational techniques for training large language models.

Welcome to the exciting dirigibles era of AI

Artificial General Ideas • 3 HN points • 30 Mar 23
🕹 Technology Innovation Artificial Intelligence Science Engineering Research
  1. The history of flight provides insights into scaling technologies like large language models in AI.
  2. Just like dirigibles were an exciting technology in their time, large language models are similarly groundbreaking today.
  3. While scaling up is important, it's also valuable to explore new directions in AI to truly advance human-like intelligence.
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GPT-5 Public Launch Expected in June

Merlinus’s Substack • 3 HN points • 25 Mar 23
🕹 Technology AI Governance Partnership Innovation
  1. GPT-5 is expected to launch in June 2023, opening up new possibilities in AI and engineering.
  2. There is a need for a public-private partnership in AI governance to ensure fairness and justice in the development and application of AI technology.
  3. Uniting public and private sectors can help AI develop in alignment with shared values, benefiting society while upholding democratic principles.

Data Science Weekly - Issue 129

Data Science Weekly Newsletter • 19 implied HN points • 12 May 16
🕹 Technology Data science Machine Learning Artificial Intelligence Programming Analytics
  1. Machine learning can help understand emoji usage and trends on social media. It's exciting to see how technology can analyze emotions expressed through simple icons.
  2. There's a growing idea that future AI may not be about creating more AI but about building platforms for people to design their own AI. This could make technology more personal and user-friendly.
  3. Automating data science processes can save time and make it easier for everyone to use machine learning effectively. Tools that simplify these tasks can be really useful for beginners.

Data Science Weekly - Issue 128

Data Science Weekly Newsletter • 19 implied HN points • 05 May 16
🕹 Technology Data science Machine Learning Artificial Intelligence Programming Neural Networks
  1. Kaggle competitions need more than just machine learning knowledge. It's important to have the right mindset and explore the data thoroughly.
  2. Neural networks are surprisingly good at compressing data. They can learn to behave effectively without being explicitly taught how.
  3. Machine learning can unintentionally reinforce social biases. It's crucial to recognize these biases and work to reduce their impact in models.

Why didn't we get GPT-2 in 2005?

DYNOMIGHT INTERNET NEWSLETTER • 3 HN points • 21 Mar 23
🕹 Technology AI Supercomputers Training Progress Competition
  1. GPT-2 likely required around 10^21 FLOPs to train, involving various estimates and approaches.
  2. The BlueGene/L supercomputer from 2005 could have trained GPT-2 in about 41 days, showcasing the progress in computing power.
  3. The development of large language models like GPT-2 was a gradual process influenced by evolving ideas, funding, and technology, distinct from targeted moon landing projects.

Data Science Weekly - Issue 127

Data Science Weekly Newsletter • 19 implied HN points • 28 Apr 16
🕹 Technology Data science Artificial Intelligence Machine Learning Statistics Programming
  1. Bayesian models can be useful for predicting future outcomes using smaller, time-stamped datasets, which may be overlooked compared to large data analysis.
  2. Visual information can highlight our mental errors and biases, suggesting that interactive graphics could help us understand our own behaviors better.
  3. Companies are quickly acquiring artificial intelligence startups to stay competitive, showing the race to lead in AI technology among major corporations.

Data Science Weekly - Issue 126

Data Science Weekly Newsletter • 19 implied HN points • 21 Apr 16
🕹 Technology Data science Machine Learning AI Programming Drones
  1. Drones are becoming easier to build and program, which can make them great hands-on projects for learning about tech.
  2. Applying data analysis techniques to literature can reveal interesting insights, like the emotional journey of characters in books.
  3. Collaborating between humans and machines often leads to better results than relying solely on one or the other.

Unpluggers etc, Part 2: Deflategate

Donkeyspace • 3 implied HN points • 10 Mar 23
🕹 Technology Artificial Intelligence Machine Learning Philosophy Literature
  1. The Deflator position questions the hype around new AI technologies, emphasizing the superficial appearance of creativity.
  2. Despite skepticism, some see the advancements in AI as a profound transformation that challenges conventional understanding.
  3. There is a conflict between the data-driven approach of recent AI models and the desire for symbolic logic for a clearer understanding of thinking.

GPT-4 has come, poor man's ChatGPT - Alpaca

AI Progress Newsletter • 3 implied HN points • 18 Mar 23
🕹 Technology AI Machine Learning Research Community Tools
  1. GPT-4 is a large multimodal model that can take text and image inputs but only gives text outputs.
  2. Alpaca offers a way to train your own ChatGPT for $100, providing easy access to powerful instruction-following LLMs.
  3. OpenAI faced criticism for not disclosing GPT-4's training data and architecture, making some NLP research projects irrelevant.

Data Science Weekly - Issue 125

Data Science Weekly Newsletter • 19 implied HN points • 14 Apr 16
🕹 Technology Data science Machine Learning Statistics Software Development Programming
  1. Platforms are important in data science because they help teams work better together and scale their projects. Good organization can make a big difference in data science tasks.
  2. Machine learning can be used to make accurate predictions, such as predicting the outcomes of sports tournaments. This can lead to impressive results in competitions.
  3. Understanding statistics is crucial in software development to assess performance and reliability. Without a solid grasp of statistics, it's hard to know how well software is performing.

Forecasting Authoritarian and Sovereign Power uses of Large Language Models

Data Taboo • 3 HN points • 13 Mar 23
🕹 Technology AI Propaganda Censorship
  1. Forecasts predict countries may develop and mandate the use of Large Language Models for censorship and propaganda by the end of 2024.
  2. There is a rising likelihood that multiple countries will produce sovereign Large Language Models by the end of 2025.
  3. There is a possibility that by the end of 2026, one country may cut off another from access to their Large Language Model as part of economic sanctions.

What's interesting about the Zed editor

Andrew's Substack • 1 HN point • 02 Aug 24
🕹 Technology Software Development Collaboration Open Source Innovation
  1. Zed is an open-source code editor and stands out because it's built in Rust, not Electron. This makes it a faster and smoother option for coding.
  2. One unique feature of Zed is 'channels,' which allow teams to collaborate on coding projects in a way that feels more like a dedicated group chat for a project.
  3. These channels are long-lived, meaning anyone can join in and help out whenever they want, making remote collaboration easier and more interactive.

Data Science Weekly - Issue 124

Data Science Weekly Newsletter • 19 implied HN points • 07 Apr 16
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Analytics
  1. Data science is important for startups and should be integrated early to help in decision-making and culture building.
  2. Machine learning can enhance user experiences, like preventing movie spoilers or predicting bus arrival times.
  3. Learning opportunities, like functional programming and specific data science skills, are available for those looking to enter the field.

Data Science Weekly - Issue 123

Data Science Weekly Newsletter • 19 implied HN points • 31 Mar 16
🕹 Technology Data science Artificial Intelligence Machine Learning Data Visualization Computer Vision
  1. Stories can help us understand the world, but not all stories are true. It's important to know when to trust our explanations and when to question them.
  2. Data science is vital for companies like Airbnb because it helps integrate analytics into leadership decisions. This shows how data can shape business strategies.
  3. Predictive data can enhance safety, like how Baidu uses map searches to forecast crowd behavior. It demonstrates how technology can help manage real-world situations.

Unpluggers, Deflators, and Mantic Pixel Dream Girls, Part 1: Why I am Not a Doomer

Donkeyspace • 3 implied HN points • 01 Mar 23
🕹 Technology AI Ethics Intelligence Philosophy Future
  1. The article discusses the debate around advanced AI potentially leading to catastrophic outcomes.
  2. It highlights the challenge of reasoning about unique, one-off events like a disaster scenario caused by AI.
  3. The author emphasizes the importance of considering different perspectives and being prepared for both negative and positive outcomes.

Data Science Weekly - Issue 122

Data Science Weekly Newsletter • 19 implied HN points • 24 Mar 16
🕹 Technology Data science Machine Learning Artificial Intelligence Analytics Statistics
  1. P-values are often seen as the gold standard for determining if a study is good, but experts warn they can be misleading and overused.
  2. Machine learning is changing how businesses operate and is being used in various real-world applications, showing its growing importance.
  3. Deep learning techniques are making big strides in generative models, helping to produce and understand complex data like images and text.

Zimop/Zcmop may-be-operations

Fprox’s Substack • 2 HN points • 15 Oct 23
🕹 Technology Extensions
  1. When designing new instructions, ensuring compatibility with older implementations can be challenging.
  2. Zimop and Zcmop introduce placeholder instructions that can be leveraged for future functionalities.
  3. These extensions may not have immediate impact, but pave the way for implementing specific features like control flow integrity in the future.

Data Science Weekly - Issue 121

Data Science Weekly Newsletter • 19 implied HN points • 17 Mar 16
🕹 Technology AI Data science Machine Learning Statistics Software Engineering
  1. A new AI with 30 years of knowledge is finally ready to be used in the real world. This shows how far AI has come in understanding and processing information.
  2. There's a new effort to monitor police behavior using algorithms to predict misconduct. This technology aims to improve police interactions with the public.
  3. Using pie charts can be misleading; better alternatives exist for visualizing data. There are effective ways to present statistics that make information clearer.

Followup To Why AI Won't Cause Unemployment

Marc Andreessen Substack • 3 HN points • 05 Mar 23
🕹 Technology AI Regulation Job Impact
  1. Technological innovation can lower prices in some sectors, like consumer electronics, while government regulation tends to raise prices in sectors like healthcare and education.
  2. AI will have a profound impact on society, but most jobs in regulated sectors are safe from AI disruption.
  3. People working in regulated sectors are essentially receiving a form of Universal Basic Income funded by consumer purchases.

GPT is Rather Good at Feed Ranking

Messy Progress • 3 HN points • 07 Mar 23
🕹 Technology AI Ranking Bias
  1. GPT makes content-based feed ranking easy and has the potential to shift ranking power to users and groups.
  2. The ChatGPT API simplifies the process of creating content-based ranking models, making it more accessible and efficient.
  3. Using large language models like GPT to generate labels for training small models can lead to practical and cost-effective approaches in content-based ranking.

Working at Google: Maps Continued

Life Since the Baby Boom • 3 HN points • 27 Feb 23
🕹 Technology Software Development Corporate culture Patents Code Reviews Project management
  1. Marissa Mayer oversaw Google's 'Local' division, focusing on local ads and services.
  2. The acquisition of Zagat by Google faced internal resistance and eventually Zagat was spun out to another company.
  3. Code reviews and the pursuit of perfection in coding can lead to conflicts and differing perspectives among software engineers.