The hottest Data science Substack posts right now

And their main takeaways
Category
Top Technology Topics

Data Science Weekly - Issue 293

Data Science Weekly Newsletter • 19 implied HN points • 04 Jul 19
🕹 Technology Data science
  1. AI is rapidly advancing, and there are important reports that analyze its progress and future implications. Staying updated can keep us informed about these changes.
  2. Machine learning is being used to translate ancient languages, bringing new opportunities to understand lost histories. This tech could unlock communication from the past.
  3. Building a strong data science portfolio and resume is crucial for job seekers in the field. Good guidance can help you showcase your skills effectively to potential employers.

Data Science Weekly - Issue 292

Data Science Weekly Newsletter • 19 implied HN points • 27 Jun 19
🕹 Technology Data science
  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 Data science
  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 290

Data Science Weekly Newsletter • 19 implied HN points • 13 Jun 19
🕹 Technology Data science
  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.

Data Science Weekly - Issue 289

Data Science Weekly Newsletter • 19 implied HN points • 06 Jun 19
🕹 Technology Data science
  1. Machine learning can create lifelike animations from just one photo, which is both impressive and a little creepy.
  2. The AI industry relies on a lot of hidden human labor, often in poor conditions, as it grows and changes how businesses operate.
  3. Training large AI models can be very harmful to the environment, producing as much carbon emissions as five cars over their lifetime.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

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

Rustic Penn • 2 HN points • 28 Apr 23
🕹 Technology Data science
  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 Data science
  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.

Data Science Weekly - Issue 287

Data Science Weekly Newsletter • 19 implied HN points • 23 May 19
🕹 Technology Data science
  1. AI is becoming better at detecting diseases like lung cancer through improved analysis of CT scans. This could help doctors make more accurate diagnoses.
  2. Robots that learn to explore their environment can contribute to advancements in artificial intelligence. Facebook believes this could lead to smarter machines for various uses.
  3. Data analysis is playing a significant role in sports, such as soccer, by helping teams like Liverpool improve their performance and achieve success.

Data Science Weekly - Issue 286

Data Science Weekly Newsletter • 19 implied HN points • 16 May 19
🕹 Technology Data science
  1. Los Angeles has significant noise pollution, mainly from airports and heavy traffic. A recent map highlights how loud different neighborhoods are.
  2. There's a growing debate on whether data can truly act as a competitive advantage for companies, especially with AI startups. It's worth questioning if real evidence supports this idea.
  3. A Swedish distillery is set to release the first whisky designed by artificial intelligence. It raises interesting questions about how AI can influence creative processes.

Data Science Weekly - Issue 285

Data Science Weekly Newsletter • 19 implied HN points • 09 May 19
🕹 Technology Data science
  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.

Data Science Weekly - Issue 284

Data Science Weekly Newsletter • 19 implied HN points • 02 May 19
🕹 Technology Data science
  1. Research on reinforcement learning is showing that agents can learn as quickly as humans by combining fast and slow learning techniques.
  2. Insurance and healthcare companies can use pictures of houses to better predict risk and improve their models.
  3. Artificial intelligence could help in designing buildings by providing new insights and alternative strategies for floor plans.

Data Science Weekly - Issue 283

Data Science Weekly Newsletter • 19 implied HN points • 25 Apr 19
🕹 Technology Data science
  1. Training neural networks can be tricky, and it's important to understand common mistakes to get good results.
  2. AI is making big waves in various fields, including music and scientific research, showing how versatile it can be.
  3. Data scientists need to know the business and the data well, or they risk becoming bottlenecked and less effective.

Data Science Weekly - Issue 282

Data Science Weekly Newsletter • 19 implied HN points • 18 Apr 19
🕹 Technology Data science
  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.

Data Science Weekly - Issue 280

Data Science Weekly Newsletter • 19 implied HN points • 04 Apr 19
🕹 Technology Data science
  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.

Local Llama

ScaleDown • 5 implied HN points • 15 Aug 23
🕹 Technology Data science
  1. Running Local Llama models can be cost-effective compared to using commercial APIs, making AI more accessible to a broader range of users.
  2. By deploying LLMs locally, users have more control over the model, allowing them to bypass limitations and ensure efficient resource utilization.
  3. Local deployment of LLMs enhances privacy and security by keeping data on the user's machine, providing an additional layer of protection.

Data Science Weekly - Issue 279

Data Science Weekly Newsletter • 19 implied HN points • 28 Mar 19
🕹 Technology Data science
  1. Three scientists won the Turing Award for their groundbreaking work on neural networks. This award is like the Nobel Prize for computing and comes with a $1 million prize.
  2. Adversarial machine learning could pose security risks by allowing enemies to reverse-engineer AI systems. Experts urge caution as this threat could impact important technologies.
  3. The fast-food giant McDonald's is investing heavily in machine learning by acquiring a startup. This shows how businesses are increasingly using data and AI to improve operations.

Data Science Weekly - Issue 278

Data Science Weekly Newsletter • 19 implied HN points • 21 Mar 19
🕹 Technology Data science
  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 277

Data Science Weekly Newsletter • 19 implied HN points • 14 Mar 19
🕹 Technology Data science
  1. Data science teams perform better with generalists instead of specialists. This approach helps teams adapt and innovate rather than just focusing on increasing productivity.
  2. R is a powerful programming language for data analysis, with many surprising capabilities beyond statistics. It has features that can impress even those in the computer science field.
  3. China is expected to surpass the U.S. in AI research output soon. This shift highlights the increasing importance of global competition in technology and research.

Data Science Weekly - Issue 276

Data Science Weekly Newsletter • 19 implied HN points • 07 Mar 19
🕹 Technology Data science
  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.

Data Science Weekly - Issue 275

Data Science Weekly Newsletter • 19 implied HN points • 28 Feb 19
🕹 Technology Data science
  1. Artificial intelligence can help humans discover things we couldn't find on our own, making it a powerful tool in various fields.
  2. Creating a strong data science portfolio and tailored resume is crucial for job seekers in the data science field to stand out to potential employers.
  3. Machine learning can significantly improve the efficiency and value of renewable energy sources like wind power, showcasing its practical applications.

Data Science Weekly - Issue 274

Data Science Weekly Newsletter • 19 implied HN points • 21 Feb 19
🕹 Technology Data science
  1. The visual search engine project for Hayneedle shows how search can be enhanced by using images instead of words. This could make finding products easier for customers.
  2. Mathematicians are starting to understand how the design of neural networks affects their capabilities. This can help in optimizing their use for various tasks.
  3. Knowing your data thoroughly is crucial for anyone working in data science. It's essential to understand where the data comes from and what it represents.

AI Builder Survey

Unsupervised Learning • 2 implied HN points • 21 Aug 24
🕹 Technology Data science
  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.

Data Science Weekly - Issue 273

Data Science Weekly Newsletter • 19 implied HN points • 14 Feb 19
🕹 Technology Data science
  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.

Data Science Weekly - Issue 272

Data Science Weekly Newsletter • 19 implied HN points • 07 Feb 19
🕹 Technology Data science
  1. Neural networks have a strong impact on their performance based on their design. Researchers are uncovering how different structures affect what they can do.
  2. There's a new Android app called Live Transcribe that helps deaf or hard of hearing people have real conversations in real time. This technology can make everyday interactions much easier.
  3. CB Insights has listed 100 of the top AI companies in the world, showcasing startups that are leading in AI technology development and innovation. This is a way to highlight the most promising players in the industry.

Data Science Weekly - Issue 271

Data Science Weekly Newsletter • 19 implied HN points • 31 Jan 19
🕹 Technology Data science
  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.

Data Science Weekly - Issue 270

Data Science Weekly Newsletter • 19 implied HN points • 24 Jan 19
🕹 Technology Data science
  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 269

Data Science Weekly Newsletter • 19 implied HN points • 17 Jan 19
🕹 Technology Data science
  1. Neural networks can be hard to understand, and researchers are exploring how to better interpret what they learn during training.
  2. In 2018, Google made significant advancements in AI research, and there's a lot for the community to reflect on and build upon going forward.
  3. Data science project flows can vary, and it's helpful for teams to structure their projects in ways that fit their unique challenges and goals.

Data Science Weekly - Issue 268

Data Science Weekly Newsletter • 19 implied HN points • 10 Jan 19
🕹 Technology Data science
  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.

Data Science Weekly - Issue 267

Data Science Weekly Newsletter • 19 implied HN points • 03 Jan 19
🕹 Technology Data science
  1. Understanding probability and statistics can be made easier with visual tools, like those offered by Seeing Theory.
  2. Machine learning has significant potential in healthcare, including improving diagnoses and assisting doctors with data.
  3. There's a strong link between social mobility and family background, suggesting our parents' status can greatly impact our own opportunities.

Data Science Weekly - Issue 266

Data Science Weekly Newsletter • 19 implied HN points • 27 Dec 18
🕹 Technology Data science
  1. Netflix's data team often clashes with the content team, highlighting the importance of balancing data insights with creative decisions.
  2. Teaching AI to write generates funny results, showcasing the difficulties of making machines understand human language.
  3. Data is not just raw information; it is influenced by human judgment and context, making it essential to analyze it carefully.

Data Science Weekly - Issue 265

Data Science Weekly Newsletter • 19 implied HN points • 20 Dec 18
🕹 Technology Data science
  1. AlphaZero is a powerful AI that learns board games like chess and Go from scratch, showing how quickly it can master complex games without prior knowledge.
  2. Building a deep learning system requires careful choice of hardware, and it's important to avoid overspending on unnecessary components.
  3. Collaboration between data science and engineering has challenges, but understanding these tension points can improve teamwork and model deployment.

Data Science Weekly - Issue 264

Data Science Weekly Newsletter • 19 implied HN points • 13 Dec 18
🕹 Technology Data science
  1. Understanding how biological intelligence works can help us create better AI. It’s all about connecting different fields like neuroscience and psychology.
  2. Laughter in the workplace can boost team success. Measuring laughter might actually help improve innovation in projects.
  3. New methods in AI allow for training models while keeping data private. This could make using sensitive information like medical records safer.

Data Science Weekly - Issue 263

Data Science Weekly Newsletter • 19 implied HN points • 06 Dec 18
🕹 Technology Data science
  1. Deep learning is rapidly evolving, and it's important to track these changes to stay updated in the field.
  2. AI is changing jobs; while some roles may vanish, there is a growing demand for skilled professionals who can work with AI.
  3. Machine learning is being used in creative ways, like predicting grocery item availability and generating addresses from satellite images.

Data Science Weekly - Issue 262

Data Science Weekly Newsletter • 19 implied HN points • 29 Nov 18
🕹 Technology Data science
  1. GANPaint allows you to create art by controlling specific objects in a scene using AI. It's an innovative way to draw, making it easier to express complex ideas visually.
  2. Uber AI has made significant progress in teaching AI to play challenging video games like Montezuma's Revenge. This shows how AI can learn and improve in tough scenarios without much human help.
  3. Amazon Comprehend Medical uses AI to understand medical language, which can help healthcare professionals work better. It's designed to help with everything from medical terms to complex procedures.

Data Science Weekly - Issue 261

Data Science Weekly Newsletter • 19 implied HN points • 22 Nov 18
🕹 Technology Data science
  1. AI tools are becoming more accessible, and new tools will help make AI more like general computing. This change could allow more people to work with AI easily.
  2. There's a strong need for better testing in data science, similar to what software developers do. Good testing can help avoid big problems from data errors.
  3. Deep learning is being explored in exciting new ways, such as detecting diseases in X-rays. These advancements could lead to better healthcare solutions.

Data Science Weekly - Issue 260

Data Science Weekly Newsletter • 19 implied HN points • 15 Nov 18
🕹 Technology Data science
  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 259

Data Science Weekly Newsletter • 19 implied HN points • 08 Nov 18
🕹 Technology Data science
  1. Seattle and Houston provided large amounts of email metadata quickly, but Seattle's request came with a twist that led to an accidental extensive data collection.
  2. A machine-learned model called FINDER is being tested to detect foodborne illnesses in real-time using web search and location data.
  3. There are innovative projects like 'dankstimate' which aim to create a cannabis price estimator similar to Zillow's home price estimates.