The hottest Software Substack posts right now

And their main takeaways
Category
Top Technology Topics

The Client Side of Over-The-Air Updates

burkhardstubert • 179 implied HN points • 15 Jan 24
🕹 Technology Software Updates Devices Engineering Industry
  1. Choosing the right over-the-air (OTA) update solution is important. Memfault was preferred because it offered better documentation and support compared to Mender.
  2. OTA updates can save time and provide quick feedback, making them more efficient than manual updates. Manual updates can be costly and lead to serious issues, especially when manufacturers have to comply with strict legal requirements.
  3. There are different strategies for implementing updates, like A/B strategies that ensure reliability and safety. It's crucial that updates work flawlessly to maintain user trust and avoid interruptions during their work.

Happy Llama Day 🦙🤩 ✨

Sector 6 | The Newsletter of AIM • 79 implied HN points • 20 Apr 24
🕹 Technology AI Computing Software Innovation Research
  1. Meta launched Llama 3, an advanced open-source language model that outshines its competitors in reasoning and coding tasks. This model is creating a lot of buzz for its performance.
  2. Andrej Karpathy, a former OpenAI scientist, is very excited about Llama 3 and thinks it will be a strong competitor against GPT-4.
  3. Llama 3 is designed with a massive 400 billion parameters, making it a powerful tool for various applications in AI.

Comprehension of Concurrency is a Lifelong Journey

Push to Prod • 19 implied HN points • 23 Jul 24
🕹 Technology Software Engineering Concurrency Debugging Systems
  1. Understanding concurrency is a long-term process that requires ongoing learning. It's normal to feel confused, but every experience adds to your knowledge.
  2. It's important to be open about your knowledge gaps. Accepting that you don't know everything helps you grow and learn from others.
  3. Mistakes and misunderstandings are part of the journey. Embracing these moments can lead to valuable insights and a deeper comprehension.

Accelerate by years part I - Inlang directories as lix repositories

Opral (lix & inlang) • 19 implied HN points • 23 Jul 24
🕹 Technology Software Development Networking Systems Programming
  1. Making inlang directories work as independent repositories can speed up the development process significantly. This means less reliance on GitHub and fewer complications.
  2. Smaller, self-contained inlang repositories require less hosting and have lower scalability needs. This makes it easier to manage and use them without needing a lot of resources.
  3. With control over push, pull, and commit actions, developers can streamline their workflows. This helps avoid many frustrating issues related to traditional version control systems.
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Rethinking Public Procurement

Arpitrage • 574 implied HN points • 15 Sep 23
💼 Business Procurement Costs Infrastructure Software Reform
  1. Government procurement often involves unnecessary costly requirements and limited bidder outreach, leading to high expenses and poor quality outcomes.
  2. High infrastructure costs in the US are exacerbated by procurement problems and a legal system that limits state power.
  3. Failure in government procurement, like outdated unemployment insurance systems, results in costly software upgrades and limited benefits for recipients.

WebVoyager AI Agent

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 23 Jul 24
🕹 Technology AI Software Web Development Autonomous Systems Machine Learning
  1. AI agents can make their own choices and decide how to reach a goal. They don’t just follow a set plan; they create their own steps as needed.
  2. These agents can try different actions and learn from the results until they find the right answer. They go through a thinking process to solve problems.
  3. While AI agents have some tools to use, they also have limits. If they can't find an answer after trying a few times, they might ask a human for help.

The Most Amazing Week in Gen AI Releases

TheSequence • 84 implied HN points • 15 Dec 24
🕹 Technology AI Software Innovation Research Modeling
  1. Several major tech companies like OpenAI, Google, and Microsoft launched new AI models in a single week. This shows how quickly AI technology is progressing.
  2. OpenAI's Sora model allows users to create videos from text descriptions, but it has some limitations. It's an exciting step for video generation!
  3. Google's Gemini 2.0 has improved capabilities, allowing it to handle more complex tasks and interact more effectively with users.

Procore

Business Breakdowns • 294 implied HN points • 27 Jun 23
💼 Business Construction Software Revenue model
  1. Procore is a leading software provider for the construction industry, offering a streamlined dashboard for developers, contractors, and architects.
  2. Procore's unique revenue model charges based on the number of modules used and total construction volume flowing through the customer's business.
  3. The company's strong market position, brand value, and low gross churn rate indicate potential for consistent growth and future profitability.

Building reliability from unreliable parts

Sunday Letters • 59 implied HN points • 12 May 24
🕹 Technology AI Cloud Software Data science Systems Engineering
  1. Modern AI systems have a random element, making them sometimes unpredictable or unreliable. This means they can give different answers even to the same question, which is a challenge for creating consistent outputs.
  2. Just like the early cloud systems, we need to use smart software solutions to make our current AI technologies more reliable. Instead of relying solely on the AI itself, we should layer software to handle and fix errors.
  3. To build better AI systems, it’s important to explore structured approaches, like guided conversations or iterative processes. This way, we can combine the strengths of AI with reliable system design.

Google's reasoning model, New open-source physics AI engine, Odyssey's Explorer, OmniAudio, AI phone calling, FACTS Leaderboard, Meta Apollo, Global Talent Network, Falcon 3, Veo 2,DeepSeek-VL2 & more

AI Brews • 17 implied HN points • 20 Dec 24
🕹 Technology AI Models Software Development Innovation
  1. Google has launched a new reasoning model called Gemini Flash Thinking that shows its thoughts, making it better at reasoning. It has top scores on the Chatbot Arena leaderboard.
  2. There is a new open-source physics simulation platform called Genesis that can help with robotics and AI applications by creating detailed, dynamic worlds.
  3. Meta has introduced a family of models called Apollo that can efficiently process long videos, and other companies are also launching new AI tools for audio and video generation.

Testing a book's code, part 6: Testing a Django project

Mostly Python • 314 implied HN points • 15 Feb 24
🕹 Technology Programming Software Testing Web Development
  1. Testing a Django project in a book involves creating a copy of the project, setting up a separate virtual environment, and ensuring it functions correctly on new Django versions.
  2. When testing a Django project, focus is usually on internal code, but the priority here is verifying functionality on new Django versions due to its frequent updates.
  3. The post discusses developing a single test function for a Django project named Learning Log, emphasizing the importance of testing project functionality as intended.

Software: Liability, Safe Harbor and National Security

Resilient Cyber • 139 implied HN points • 08 Feb 24
🕹 Technology Cybersecurity Software National Security Innovation
  1. Software developers may need to be held responsible for security flaws that lead to cyber attacks. This could protect critical infrastructure from being misused.
  2. Creating clear standards for software safety is important. These rules could help developers understand what they're responsible for and how to improve their products.
  3. A safe harbor could protect developers who follow best practices. This means they won't face lawsuits if they do everything right and still have issues.

Favorable Winds for AMD in the GenAI Chip Market

Gradient Flow • 139 implied HN points • 08 Feb 24
🕹 Technology Hardware AI Software Privacy Analytics
  1. AMD's hardware offers performance and efficiency gains for AI tasks, with specialized optimizations making them well-suited for training and inference in advanced AI scenarios.
  2. AMD has invested in mature and optimized open-source software like the ROCm stack, providing a critical foundation for maximizing the performance of their hardware in real-world AI applications.
  3. Market trends are aligning favorably for AMD, with shorter lead times improving chip availability, notable endorsements from industry leaders, and growing momentum indicating a strong position in the AI silicon landscape.

Apple Intelligence is Not a ChatGPT Wrapper

Sector 6 | The Newsletter of AIM • 39 implied HN points • 11 Jun 24
🕹 Technology AI Software Privacy Partnerships Mobile
  1. Apple is focusing on something called 'Apple Intelligence' instead of just machine learning. This new AI focuses on privacy, which is an important issue for users.
  2. Apple has teamed up with OpenAI to integrate ChatGPT into its devices. This means Siri can now use ChatGPT's features to help users.
  3. Users will be warned before they send any personal information or queries to ChatGPT. This helps keep their data safe.

"Organic Markdown" Intro

Rethinking Software • 199 implied HN points • 21 Aug 24
🕹 Technology Programming Software Development Documentation Open Source
  1. Organic Markdown helps keep your code and documentation in sync. This means you won't have to edit your code separately from your notes, making everything easier to manage.
  2. It improves how your code is presented. By arranging your code better for people to understand, you can still adjust it later for the computer to run.
  3. You can run commands and build applications right from your Markdown file. This makes the workflow smoother and lets you focus more on coding.

A Closer Look Into Databricks's Photon Engine

VuTrinh. • 79 implied HN points • 13 Apr 24
🕹 Technology Software Data Engineering Database Systems Cloud Computing Artificial Intelligence
  1. Photon engine uses columnar data layout to manage memory efficiently, allowing it to process data in batches. This helps in speeding up data operations.
  2. It supports adaptive execution, which means the engine can change how it processes data based on the input. This can significantly improve performance, especially when data has many NULLs or inactive rows.
  3. Photon integrates with Databricks runtime and Spark SQL, allowing it to enhance existing workloads without completely replacing the old system, making transitions smoother.

Frame Rate, experiments, messes

Sunday Letters • 39 implied HN points • 09 Jun 24
🕹 Technology AI Innovation Software Engineering Learning
  1. AI technology is developing quickly, and if you don’t engage with it yourself, you might be caught off guard by new advancements. It's better to stay updated by trying things out.
  2. Many people still don’t experience AI firsthand and only learn about it from news. Trying out tools like GPT-4 can help you understand its potential.
  3. Being spontaneous and messy in your approach is key to creativity. Don't worry about making things perfect; experimentation can lead to great innovations.

Obvious Business Opportunities

In My Tribe • 425 implied HN points • 09 Mar 24
🕹 Technology Software Customer Support Robots AI
  1. Addressing technical debt in outdated software systems is a significant business opportunity, especially using new pattern-matching models to optimize and secure old software.
  2. Leveraging large language models (LLMs) for customer support improvement and developing efficient back-office apps for various sectors presents lucrative business prospects.
  3. Special-purpose robots tailored for specific tasks like security or medical procedures offer practical business opportunities compared to humanoid robots.

THINK's Lightspeed C

Computer Ads from the Past • 512 implied HN points • 27 Sep 23
🕹 Technology Computers Programming Software Tech Companies Computer History
  1. Lightspeed C was a C programming language software developed in the mid-1980s for Atari systems and Macintosh computers.
  2. Clearstar Softechnologies created Lightspeed C for Atari systems in 1985, and the company was later purchased by Omega Soft in 1988.
  3. THINK Technologies released Lightspeed C for Mac and later renamed it to THINK C in the mid-1980s, receiving positive reviews for its speed and user-friendliness.

Database Wars, Insane SQLite Facts, Static Search Trees Optimized, & More

HackerPulse Dispatch • 8 implied HN points • 07 Jan 25
🕹 Technology Databases AI Engineering Software Performance
  1. Static search trees are great for quick data searching. They are built for data that doesn't change much, making them much faster than regular search methods.
  2. AI can't build strong engineering teams on its own. Engineers need to take action and push for programs that help train and mentor new hires.
  3. SQLite is a super popular database used by millions, but it's managed by just a small team. Its simplicity and reliability make it a favorite for many applications.

Making Sense of Agentic AI | ThoughtWorks’ Birgitta Boeckeler

Dev Interrupted • 28 implied HN points • 12 Nov 24
🕹 Technology AI Software Programming Development Automation
  1. AI tools can help software teams improve their work, but it's important to pick the right ones that actually make a difference. Sometimes the hype around AI doesn't match up with real-world results.
  2. Governance matters when it comes to programming languages. A strict control model can limit a language's potential for growth, so a more open approach might be better.
  3. Reddit is gaining popularity as users appreciate its less polished, more authentic content. It shows that not all platforms need to rely heavily on AI to attract people.

Building The Most Basic LangChain Chatbot

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 59 implied HN points • 06 May 24
🕹 Technology AI Software Chatbots NLP Data
  1. Chatbots use Natural Language Understanding (NLU) to figure out what users want by detecting their intentions and important information.
  2. With Large Language Models (LLMs), chatbots can understand and respond to conversations more naturally, moving away from rigid, rule-based systems.
  3. Building a chatbot now involves using advanced techniques like retrieval-augmented generation (RAG) to pull in useful information and provide better answers.

Phi-3, your Pocket LLM!

Aziz et al. Paper Summaries • 79 implied HN points • 29 Apr 24
🕹 Technology AI Machine Learning Hardware Software Data science
  1. Microsoft's Phi-3 is a new AI model that is small enough to run on your phone, yet still performs well. This is a big deal because most AI models are too large for personal devices.
  2. The model uses high-quality, filtered data for training, focusing on reasoning and educational materials. This approach makes Phi-3 better at understanding rather than just memorizing facts.
  3. Even though Phi-3 is powerful, it has some limitations, like not being multilingual. There are also tasks it struggles with, like those needing lots of factual knowledge.

The Astera Labs Extinction Event

Irrational Analysis • 99 implied HN points • 10 Mar 24
🕹 Technology Semiconductors Connectivity Networking Hardware Software
  1. Astera Labs focuses on making "extender" chips called retimers, which enable design flexibility and cost savings by allowing the use of cheaper PCB materials.
  2. Understanding technical terms like SerDes, PCB stackup, signal integrity, loss, reflections, CTLE, DFE, jitter, adaptation, and CDR bandwidth is crucial in the semiconductor industry.
  3. Broadcom's recent product announcements have positioned them as a strong competitor to Astera Labs, showcasing superior power efficiency, compatibility, reach, and overall competitive advantages.

What Is a Software Simulator?

CodeYam’s Substack • 39 implied HN points • 04 Jun 24
🕹 Technology Software Simulations AI Testing Automation
  1. Simulators are valuable tools leveraged by inventors and engineers throughout history to test ideas quickly and gain insights into complex problems.
  2. A robust software simulator has qualities like a simulated environment, scenarios, isolation, and automation, which can significantly speed up the software development process.
  3. Software simulators allow testing how software performs in various scenarios, enabling faster delivery of high-quality products without the need for extensive manual testing.

Democratizing AI: MosaicML's Impact on the Open-Source LLM Movement

Deep (Learning) Focus • 255 implied HN points • 03 Jul 23
🕹 Technology AI Open Source Software Models Training
  1. Creating a more powerful base model is crucial for improving downstream applications of Large Language Models (LLMs).
  2. MosaicML's release of MPT-7B and MPT-30B has revolutionized the open-source LLM community by offering high-performing, commercially-usable models for practitioners in AI.
  3. MPT-7B and MPT-30B showcase innovations like ALiBi, FlashAttention, and low precision layer norm, leading to faster training, better performance, and support for longer context lengths.

What I Learned This Week #2

Eventually Consistent • 39 implied HN points • 02 Jun 24
🕹 Technology Software Concurrency Performance Podcasts
  1. Transaction latency is crucial in datacenters, affected by shared resource contention that causes waiting, the main performance bottleneck.
  2. Coroutines provide concurrency without synchronization complexity, unlike threads which need careful synchronization for shared data access to avoid conflicts.
  3. Each thread maintains its own call stack, recording function calls and variables, enabling independent execution and function history maintenance.

CodeGen News for 2024-09-09

CodeGen News • 3 HN points • 09 Sep 24
🕹 Technology AI Software Coding Development Tools
  1. There are new articles and tools to help developers work better with AI-generated code. It's important to stay updated on these resources to improve your skills.
  2. The newsletter features a variety of reading, watching, and listening materials that can enhance your understanding of AI in coding. Exploring different formats can make learning more engaging.
  3. Recent updates to coding projects, like GitHub Copilot and Replit, show how AI is changing software development. Keeping track of these changes can help you utilize these tools effectively.

AI Roundup 093: Diminishing returns

Artificial Ignorance • 29 implied HN points • 15 Nov 24
🕹 Technology AI Machine Learning Software Data science Innovation
  1. Big AI companies are realizing that just making their models bigger doesn't always improve their performance. They're facing challenges because the quality of training data is more important than simply using more computing power.
  2. AI companies need to create new ways to measure performance since the old benchmarks are outdated. This lack of standard testing makes it hard for people to compare how different AI models stack up against each other.
  3. AI-generated art is becoming more popular and accepted in the market. A recent artwork sold for a lot of money, showing that people are starting to appreciate creations made by AI, even though it raises questions about what creativity really means.

Why did Microsoft give GitHub Copilot away for free?

Brick by Brick • 9 implied HN points • 26 Dec 24
🕹 Technology AI Tools Software Developer Tools Monetization Ecosystem
  1. Microsoft offered GitHub Copilot for free to protect its platform from competitors. By making it free, they keep developers engaged and less likely to switch to other tools.
  2. Copilot boosts developer productivity but can also distract from GitHub's core services. Microsoft hopes that by offering it for free, developers will stay loyal to GitHub instead of looking elsewhere.
  3. This strategy makes it hard for smaller companies to compete since they can't match a free product. It helps Microsoft maintain control over the developer market and promote its other services.

Why Companies Become Stuck In Bad Coding Loops—And How To Escape Them

Wisdom over Waves • 219 implied HN points • 31 Oct 23
🕹 Technology Software Coding Tech industry Development Innovation
  1. Companies can get stuck in bad coding loops due to shortcuts taken to meet deadlines and lack of focus on code fitness, leading to slow progress and accumulation of bad-quality code
  2. Two loops of bad coding involve creating technical debt with more code and lowering hiring bar due to pressure, resulting in slower progress and accumulation of bad code practices
  3. To break out of these loops, companies can freeze code hotspots, raise hiring bar, upskill developers, and reduce technical debt through mission-critical task forces

Krutrim 101: Learning to Have Fun

Sector 6 | The Newsletter of AIM • 99 implied HN points • 02 Mar 24
🕹 Technology AI Chatbots Language Models Software Innovation
  1. Krutrim is India's first chatbot using large language model technology, designed to support multiple Indic languages. It's being praised and criticized, but the focus should be on having fun with it.
  2. The chatbot can understand 22 languages and respond in 10, making it unique for the Indian audience. Some claims suggest it even outperforms popular models like GPT-4 for these languages.
  3. People are encouraged to enjoy using Krutrim instead of taking any criticism or praise too seriously. It's about exploring and having fun with the technology.