The hottest Software Development Substack posts right now

And their main takeaways
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Top Technology Topics

Data Science Weekly - Issue 322

Data Science Weekly Newsletter • 19 implied HN points • 23 Jan 20
🕹 Technology Artificial Intelligence Data science Machine Learning Software Development Information Systems
  1. Smule is a popular karaoke app and now has a feature called Smulemates that helps users find others with similar singing styles to sing with.
  2. Facebook AI made a big advancement with a new learning algorithm called DD-PPO that helps machines navigate real-world environments using just basic tools like GPS and cameras.
  3. There’s a tool called Manifold from Uber that helps people check if their machine learning models are working well, and they have made it open source for everyone to use.

Data Science Weekly - Issue 314

Data Science Weekly Newsletter • 19 implied HN points • 28 Nov 19
🕹 Technology AI Data science Machine Learning Programming Software Development
  1. Data science can be quite tedious and involves a lot of boring tasks. It's important for aspiring data scientists to manage their expectations and be prepared for the long-term commitment.
  2. AI is changing the workplace, especially for white-collar jobs. Many roles in fields like law, marketing, and programming might be disrupted by advancements in artificial intelligence.
  3. Diversity in AI isn't just a technical issue; it's about understanding perspectives and the impact of pronouns and identity in discussions on diversity.

Dependency Injection Demystified

Jacob’s Tech Tavern • 3 HN points • 06 Jun 23
🕹 Technology Programming Testing Architecture Networking Software Development
  1. Unit testing helps in writing maintainable code by separating concerns and breaking code into manageable chunks.
  2. Modern language features like async/await and functional reactive programming provide great coding ergonomics but require careful testing to avoid flakiness.
  3. Dependency Injection separates the tasks of gathering ingredients and cooking, making code more testable and maintainable.

Data Science Weekly - Issue 310

Data Science Weekly Newsletter • 19 implied HN points • 31 Oct 19
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Analytics
  1. Rising sea levels could affect more cities than we realized, based on new research using artificial intelligence to correct earlier mistakes.
  2. Machine learning has made it possible to solve complex math problems, like the three-body problem, much faster than before.
  3. AI can learn to play video games like StarCraft II at a high level by practicing against itself, showcasing advances in gaming and strategy development.

Data Science Weekly - Issue 306

Data Science Weekly Newsletter • 19 implied HN points • 03 Oct 19
🕹 Technology AI Data science Machine Learning Software Development Computer Science
  1. Data scientists are in high demand, and platforms like Vettery can help connect them with top employers. It’s a good time to create a profile and name your salary.
  2. New developments in AI are making it easier for algorithms to understand natural language and plan tasks effectively. This approach could lead to smarter AI capable of tackling unfamiliar challenges.
  3. The training process for Generative Adversarial Networks (GANs) is often tricky, but researchers are working on methods to stabilize it. This could improve how GANs are used in various applications.
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Data Science Weekly - Issue 305

Data Science Weekly Newsletter • 19 implied HN points • 26 Sep 19
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Data Analysis
  1. Neural networks can create unique artworks, like an unseen Picasso painting, by analyzing and reconstructing based on existing styles.
  2. Explainable AI is important for understanding how AI models make decisions, especially to avoid biases and harmful behaviors.
  3. Anonymous data can still lead to re-identification, meaning privacy is a big concern even when personal information is removed.

Data Science Weekly - Issue 302

Data Science Weekly Newsletter • 19 implied HN points • 05 Sep 19
🕹 Technology Artificial Intelligence Data science Machine Learning Software Development Research
  1. Deep learning is a big deal in AI. It's all about machines learning from data, and experts like Yann LeCun are leading the way.
  2. Data scientists are in high demand, and understanding their salaries can help you know what to expect in the job market.
  3. Using AI for face recognition can be surprising, like tracking chimpanzees, and shows how powerful this technology has become.

Data Science Weekly - Issue 301

Data Science Weekly Newsletter • 19 implied HN points • 29 Aug 19
🕹 Technology Data science AI Machine Learning Software Development Research
  1. Managing data scientists requires unique skills and knowledge that differ from other management roles. It's important for leaders to understand these differences for effective team building.
  2. Research in data science is a long-term commitment, not a quick task. Success often comes from persistence and adaptation over time.
  3. Creating a strong resume for data science roles is crucial. It can be challenging to know what to include, so seeking specific advice is helpful.

Data Science Weekly - Issue 299

Data Science Weekly Newsletter • 19 implied HN points • 15 Aug 19
🕹 Technology AI Data science Machine Learning Software Development Analytics
  1. AI is now being used to train models for games like video soccer, building on its success in chess and Go. This shows how far AI technology has come in mastering complex tasks.
  2. Nvidia has made big strides in AI by speeding up the training process for advanced language models. This improvement can help in developing better conversational AI systems.
  3. To become a data scientist, it's more effective to start in a related job and learn along the way. Focusing too much on skills from blog posts can lead to confusion and delay.

Data Science Weekly - Issue 298

Data Science Weekly Newsletter • 19 implied HN points • 08 Aug 19
🕹 Technology AI Data science Machine Learning Software Development Natural Language
  1. AI is becoming a part of dating apps, helping users find potential matches by analyzing their conversations.
  2. Natural Language Processing is evolving, with new trends emerging from major conferences like ACL 2019.
  3. Tools like Teraport simplify the process of building data pipelines, making it easier to manage data for machine learning projects.

NeuralNextG v0.1.0: Analyzing Rocket League Games automatically with Machine Learning

joeydotcomputer’s Substack • 1 HN point • 19 Feb 23
🕹 Technology Machine Learning Data Analysis Gaming Analytics Software Development
  1. The project analyzed 200,000 Rocket League games with a neural network to predict scoring probabilities.
  2. The tool NeuralNextG can provide analysis frame-by-frame and aims to expand into coaching, scouting, win probabilities, and detecting smurfs/bots.
  3. The potential business model suggests integrating analytics tools like NeuralNextG into free-to-play games for users to pay for personalized data services.

Securing Cloud-Based CI Systems: Best Practices

Iceberg • 1 HN point • 30 Sep 23
🕹 Technology Cloud Computing Cybersecurity Software Development DevOps
  1. Limit who or what can invoke processes in CI systems to reduce the blast radius.
  2. Utilize separate cloud and saas accounts for different environments to enhance security and avoid errors.
  3. Regularly monitor dependency security, distinguish between CI and deployment contexts, and minimize reliance on third-party systems for supply chain risk mitigation.

How to use an Object Relational Mapper and never learn SQL

Bad Software Advice • 1 HN point • 04 Mar 24
🕹 Technology Programming Languages Frameworks Libraries Software Development
  1. SQL can be intimidating, but using Object Relational Mappers (ORM) allows you to work with objects in memory instead of worrying about SQL intricacies.
  2. Abstraction in software, like using ORM, lets you hide the complexity of data management and focus more on coding comfortably.
  3. There are many ORM options available for various programming languages, each with cool names, making it easier to work with databases without diving deep into SQL.

Data Science Weekly - Issue 296

Data Science Weekly Newsletter • 19 implied HN points • 25 Jul 19
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Data Analysis
  1. Machine learning is being used in various industries to improve data handling and application. There's a growing trend of using Python notebooks for these projects.
  2. Facebook created a tool called Map With AI to help speed up the mapping of roads, especially in less-developed areas. It uses satellite imagery to predict road networks.
  3. Leaderboards in Natural Language Processing (NLP) encourage teams to compete, which drives the development of better models for understanding human language.

SaaS: The Lazy Industry

Alex Ghiculescu's Newsletter • 4 HN points • 07 Apr 23
💼 Business SaaS Software Development Innovation Competition Product Management
  1. SaaS companies prioritize cash flow over product improvements, leading to less investment in innovation.
  2. The high cost of software production creates strong moats for B2B companies, making it challenging for competitors to enter the market.
  3. To avoid becoming 'lazy,' companies can focus on disciplined spending, lean teams, and continuous innovation.

Resizing the Mac App Store: a tale of regret & redemption

awesomekling • 3 HN points • 19 Apr 23
🕹 Technology Software Development Performance optimization
  1. Performance optimization involves investigating and addressing subsystems like layout, style recalculation, and JavaScript execution.
  2. Efforts to optimize can lead to useful general optimizations, not just specific to the initial use case.
  3. Facing challenges and learning from failures can lead to growth and eventual success in overcoming technical hurdles.

Data Science Weekly - Issue 292

Data Science Weekly Newsletter • 19 implied HN points • 27 Jun 19
🕹 Technology AI Data science Machine Learning Robotics Software Development
  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.

Data Science Weekly - Issue 291

Data Science Weekly Newsletter • 19 implied HN points • 20 Jun 19
🕹 Technology AI Machine Learning Data science Robotics Software Development
  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.

Data Science Weekly - Issue 282

Data Science Weekly Newsletter • 19 implied HN points • 18 Apr 19
🕹 Technology Data science Machine Learning Software Development Artificial Intelligence Computing
  1. Machine learning applications can be limited by a lack of computing power. Many teams have ideas they want to explore, but they can't because their current systems can’t handle the demands.
  2. Estimating the time needed for software projects is challenging and often leads to underestimating. It's important to consider statistical factors that can affect project timelines.
  3. Focusing solely on the performance of a machine learning model can be a mistake. It's better to look at how the model fits into a larger system and how it interacts with other components.

Segmentation Tooling winners + new $50,000 prize!

Vesuvius Challenge • 3 implied HN points • 27 Jun 23
🕹 Technology Software Development Open Source Data Visualization Programming
  1. There is a $50,000 Segmentation Tooling Prize to incentivize the building of open source software to help segment scrolls.
  2. The winners of the first prize developed innovative tools like Optical Flow Segmentation and Khartes.
  3. A new $50,000 Segmentation Tooling Prize 2 has been announced with a deadline of September 15, 2023.

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.

Data Science Weekly - Issue 270

Data Science Weekly Newsletter • 19 implied HN points • 24 Jan 19
🕹 Technology Data science Artificial Intelligence Machine Learning Robotics Software Development
  1. Curiosity in data science can lead to big innovations. Instead of just focusing on improving processes, companies should give data scientists the space to explore new ideas.
  2. AI technology is advancing but can also reinforce past mistakes, especially in areas like criminal justice. It's important to use this technology wisely to avoid repeating errors.
  3. Training resources for aspiring data scientists are crucial. Guides that help build a strong portfolio and craft impressive resumes can significantly improve job prospects in this field.

Data Science Weekly - Issue 268

Data Science Weekly Newsletter • 19 implied HN points • 10 Jan 19
🕹 Technology Data science Machine Learning Artificial Intelligence Deep Learning Software Development
  1. Being a specialist is important in data science. It's better to focus on a specific area rather than trying to know a little about everything.
  2. Machine learning research often takes a long time to reach actual industries. Many cutting-edge advancements are not quickly applied in real-world scenarios.
  3. Understanding practical skills is crucial for success in machine learning jobs. Many candidates lack essential skills that aren't taught in standard courses.

Announcing posetree.py: Wrangling Timestamps and Transforms for Robots

General Robots • 2 HN points • 10 Jul 23
🕹 Technology Robotics Programming Open Source Mathematics Software Development
  1. Posetree.py is a library for dealing with poses and transforms in robotics, making code more readable and reducing common bugs.
  2. Understanding the distinction between transforms, poses, and frames is crucial for clarity in robotics code.
  3. The 'timestamps' capability of posetree.py allows for expressing powerful ideas with simple code by automatically handling frame motion.

Snowflake Summit 2023

Magis • 2 HN points • 02 Jul 23
🕹 Technology Cloud Computing Software Development Cybersecurity Data Governance
  1. Snowflake Summit 2023 introduced key features including a partnership with Nvidia, Snowpark Container Services for machine learning, and updates to the Native Application Framework.
  2. Snowflake announced new options for paying Marketplace Listings using Snowflake capacity contracts, custom billing events for native applications, and data governance features like Aggregation Constraints.
  3. Additional announcements at Snowflake Summit 2023 included updates in Snowflake SQL, a new Snowflake Performance Index, and the ability to set spending alerts and calculate cost run-rates.

Data Science Weekly - Issue 260

Data Science Weekly Newsletter • 19 implied HN points • 15 Nov 18
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Analytics
  1. There are great resources available for learning machine learning, making it easier to find information without re-searching. A collection of favorite resources can be helpful for quick reference.
  2. Seasonality in markets can impact demand, and companies like Lyft develop tools to encourage usage during peak times. Predicting when to activate these tools can help balance the supply of drivers and passengers.
  3. Making the shift from graduate student to data scientist can be challenging, but perseverance and learning from setbacks are crucial. Many find success by staying focused and adapting their skills to the job market.

Data Science Weekly - Issue 258

Data Science Weekly Newsletter • 19 implied HN points • 01 Nov 18
🕹 Technology Data science Machine Learning Artificial Intelligence Programming Software Development
  1. Reinforcement learning agents can now explore better with curiosity-driven methods, helping them perform beyond human levels in certain games.
  2. Machines can simulate dreaming by recognizing patterns like the human brain, allowing them to create unique visual outputs without direct input.
  3. Choosing the right data science projects is crucial; a good strategy can lead to valuable results while a poor one may just waste resources.

Gorilla LLM: Bridging APIs with User-Specified Tasks

Sudo Apps • 2 HN points • 15 Jun 23
🕹 Technology AI APIs Machine Learning Software Development Artificial Intelligence
  1. Gorilla LLM is designed to connect large language models with various services and applications through APIs.
  2. LLaMA was chosen as the base model for Gorilla, which has since been fine-tuned with GPT-4, GPT-3.5, and other models.
  3. Gorilla LLM introduces novel concepts like retriever-aware training and AST sub-tree matching for more accurate inferences.

Data Science Weekly - Issue 253

Data Science Weekly Newsletter • 19 implied HN points • 27 Sep 18
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Programming
  1. Uber uses forecasting with machine learning and deep learning to enhance its products and services. This means they can predict customer needs better and improve their offerings based on accurate data.
  2. Deep learning is changing software development by requiring fewer lines of code. Instead of writing complicated rules, developers set a foundation and let the system learn from examples.
  3. AI is being influenced by how we sense smell, leading to advancements in both biology and technology. Understanding chemical information can help create more sophisticated AI systems.

Data Science Weekly - Issue 249

Data Science Weekly Newsletter • 19 implied HN points • 30 Aug 18
🕹 Technology Data science Machine Learning Artificial Intelligence Big Data Software Development
  1. Netflix is using notebooks for development and collaboration, helping manage many scheduled jobs more effectively.
  2. Understanding the world in 3D is challenging, especially for extending successful technologies like convolutional networks.
  3. There's a creative idea to enhance shopping experiences for color-blind clients by pairing their selections with personalized music.

Data Science Weekly - Issue 248

Data Science Weekly Newsletter • 19 implied HN points • 23 Aug 18
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Analytics
  1. AI is changing how we do business, and it's becoming more self-sufficient, meaning it could improve processes on its own without needing human input.
  2. China uses data and AI extensively for surveillance and governance, which raises questions about the balance between democracy and data-driven control.
  3. New tools and technologies are constantly emerging in data science, such as those that help improve the speed of medical procedures like MRIs and enhance gaming graphics.