The hottest Technology Substack posts right now

And their main takeaways
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Top Technology Topics

[in case you missed it] Data Science Weekly - Issue 323

Data Science Weekly Newsletter • 0 implied HN points • 01 Feb 20
🕹 Technology Data science Machine Learning Artificial Intelligence Deep Learning Statistics
  1. Cleaning and organizing data takes a lot of time for data scientists, and lack of access to good data can stop many projects from happening.
  2. Using a checklist can help data scientists keep track of all the necessary steps in their projects, making their work less overwhelming.
  3. Learning progressively with simpler concepts first can help both humans and machine learning models tackle more complex problems effectively.

Untrusted smart models and trusted dumb models

Redwood Research blog • 0 implied HN points • 07 May 24
🕹 Technology AI Safety Models Alignment Protocol
  1. The most reasonable strategy to assess if AI models are deceptively aligned is to test their capability; incompetent models are less likely to be deceptively aligned.
  2. By using capability evaluations, models tend to fall into categories of untrusted smart models and trusted dumb models.
  3. Combining dumb trusted models with limited human oversight can help mitigate the risks posed by untrusted smart models.

Access to powerful AI might make computer security radically easier

Redwood Research blog • 0 implied HN points • 10 Jun 24
🕹 Technology AI Monitoring
  1. Access to powerful AI could significantly simplify computer security by automating monitoring and flagging suspicious activities before they cause harm.
  2. Trust displacement by utilizing AI for tasks that could pose security risks if performed by humans can enhance security measures.
  3. Fine-grained permission management with AI could improve security by efficiently handling complex security policies that humans find cumbersome.

[in case you missed it] Data Science Weekly - Issue 320

Data Science Weekly Newsletter • 0 implied HN points • 12 Jan 20
🕹 Technology AI Data science Machine Learning Consulting Research
  1. Creating successful data projects needs careful planning. It's not just about getting the model right; you have to think about the project's context and how it fits into the bigger picture.
  2. AI is speeding up material discovery significantly. Researchers are using AI to create new materials much faster than traditional methods, which could change many industries.
  3. Data lakes offer flexibility in storing data. Unlike data warehouses that require strict definitions, data lakes allow for various data types and structures, making them adaptable but also posing some challenges.

[in case you missed it] Data Science Weekly - Issue 318

Data Science Weekly Newsletter • 0 implied HN points • 28 Dec 19
🕹 Technology Data science Machine Learning AI Visualization Programming
  1. Data visualization tools help us understand complex data better. New projects like VisualizeMnist and butterfly datasets show exciting ways to use these tools.
  2. AI is becoming powerful in games, as seen with Pluribus, an AI that beats professional poker players. This success highlights the advancements in AI competition.
  3. Learning the math behind neural networks is important. Resources are available to help demystify the concepts, making it easier for beginners to grasp.
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[in case you missed it] Data Science Weekly - Issue 317

Data Science Weekly Newsletter • 0 implied HN points • 21 Dec 19
🕹 Technology Artificial Intelligence Machine Learning Data science Robotics Computer Science
  1. NeurIPS 2019 showcased a lot of innovation in AI, with numerous workshops and papers highlighting current research trends.
  2. AI benchmarks, like games, are not always the best way to measure intelligence because they don't truly represent problem-solving skills.
  3. There are new advancements in AI that improve how machines learn and respond, such as handling complex games and understanding language better.

[in case you missed it] Data Science Weekly - Issue 316

Data Science Weekly Newsletter • 0 implied HN points • 14 Dec 19
🕹 Technology Data science Machine Learning Programming Artificial Intelligence Statistical Analysis
  1. NeurIPS 2019 saw a huge increase in submissions, with an acceptance rate of 21.6%. This highlights the growing interest and importance of data science research.
  2. Many data science teams use both R and Python, which can create challenges. Finding ways to combine these languages is key to enhancing team collaboration.
  3. Training projects like predicting dog adoption outcomes and understanding game strategies show the real-world applications of data science in improving lives and decision-making.

Managing catastrophic misuse without robust AI

Redwood Research blog • 0 implied HN points • 07 May 24
🕹 Technology AI Security Ethics Cybercrime Monitoring
  1. Managing catastrophic misuse of powerful AIs requires strategies to ensure they refuse tasks with potential for harm.
  2. Dealing with bioterrorism misuse may involve creating separate API endpoints, stringent user checks, and monitoring for suspicious activities.
  3. Mitigating large-scale cybercrime with AI may involve monitoring, human auditing, and banning users based on suspicious behavior.

Catching AIs red-handed

Redwood Research blog • 0 implied HN points • 07 May 24
🕹 Technology AI Safety measures
  1. Catching AIs red-handed changes the situation significantly, making it harder for the model to escape and enabling promising ways to prevent future escape attempts.
  2. Planning to shut down a model if caught scheming can be a sensible approach to ensure safety, even before deploying it.
  3. Developing techniques for few-shot catastrophe prevention is important, as catching escape attempts can provide valuable insights for improving safety and evaluating countermeasures.

AI catastrophes and rogue deployments

Redwood Research blog • 0 implied HN points • 03 Jun 24
🕹 Technology AI Safety Security
  1. Categorizing AI catastrophes based on rogue deployments or lack thereof is crucial for understanding safety measures and potential threats.
  2. Rogue deployments, where safety measures are absent, pose a significant risk as they make causing a catastrophe much easier compared to non-rogue deployments.
  3. Different attacker profiles like scheming AIs, lab insiders, and external attackers play a key role in determining the type and severity of AI-related catastrophes.

[in case you missed it] Data Science Weekly - Issue 315

Data Science Weekly Newsletter • 0 implied HN points • 07 Dec 19
🕹 Technology AI Machine Learning Data science Neural Networks Data Visualization
  1. AI technology is helping scientists study animals better, but it's also creating a lot of data that needs managing. There are smart solutions emerging to help handle this data overload.
  2. Machine learning platforms are still quite complicated and unique, making it hard for researchers to reproduce results. There's a need for more simplicity and standardization in these tools.
  3. Recent studies using machine learning have uncovered new insights into classic literature, revealing which parts of Shakespeare's plays may have been written by others. This shows the power of AI in analyzing texts.

[in case you missed it] Data Science Weekly - Issue 313

Data Science Weekly Newsletter • 0 implied HN points • 23 Nov 19
🕹 Technology AI Machine Learning Data science Cloud Computing Programming
  1. Google Cloud is improving AI transparency by explaining how data influences machine learning decisions. This helps companies understand AI outputs better.
  2. Sony is launching a new AI division to compete with big players like Google and Facebook for talent and projects. This shows that the AI race is heating up.
  3. It's important to differentiate between real AI and fake claims. Many products marketed as AI may not actually work as promised, so being cautious is key.

[in case you missed it] Data Science Weekly - Issue 312

Data Science Weekly Newsletter • 0 implied HN points • 16 Nov 19
🕹 Technology Data science Artificial Intelligence Machine Learning Statistics Neuroscience Research
  1. Researchers are discovering ways to turn brain signals into speech, which could change how people communicate.
  2. There's a growing concern about bias in AI systems, and finding solutions is important to ensure fairness.
  3. Data scientists are highly sought after in the job market, highlighting the importance of skills in data analysis and machine learning.

[in case you missed it] Data Science Weekly - Issue 310

Data Science Weekly Newsletter • 0 implied HN points • 02 Nov 19
🕹 Technology Data science Machine Learning Artificial Intelligence Research Statistics
  1. Rising sea levels are going to affect more cities than we thought, and scientists are using AI to improve predictions about future coastlines.
  2. A new neural network can solve a difficult math problem much faster than before, showing how machine learning can change traditional math approaches.
  3. DeepMind's AI has learned to play StarCraft II better than most human players, using self-cooperation to develop new strategies in the game.

[in case you missed it] Data Science Weekly - Issue 309

Data Science Weekly Newsletter • 0 implied HN points • 26 Oct 19
🕹 Technology Data science Artificial Intelligence Machine Learning Quantum Computing Genetics
  1. A new gene editing method called prime editing has been developed, making changes to DNA easier and more accurate.
  2. Teaching rats to drive small cars has shown that learning complex tasks can help reduce stress and improve mental abilities in these animals.
  3. Researchers are making strides in quantum computing, claiming they have achieved a significant milestone that proves a programmable quantum computer can perform useful tasks.

What is Surgical Fine-Tuning and Why You Should Care

Three Data Point Thursday • 0 implied HN points • 13 Jul 23
🕹 Technology AI Data Modeling Deep Learning Estimation
  1. Surgical fine-tuning in ML makes algorithms better suited for specific business contexts through precise changes, an advancement over regular fine-tuning.
  2. Entity-centric data modeling marries ML feature engineering with data engineering, improving data operations for companies.
  3. Estimating efforts for ML projects can be simplified by considering the cost of delay and the real-time requirement of the algorithm.

You're Like a Wizard, Samwell

The Unabashed Observer • 0 implied HN points • 09 Feb 24
🕹 Technology Digital Revolution Social media influence Technology impact
  1. Throughout history, access to information has changed - from only the nobility to now widespread literacy.
  2. As technology evolved, the way we share information has changed, decreasing costs and making distribution easier.
  3. In the modern era, the rise of social media has shifted the power of information dissemination, highlighting the challenge between fact and fiction.

[in case you missed it] Data Science Weekly - Issue 307

Data Science Weekly Newsletter • 0 implied HN points • 12 Oct 19
🕹 Technology Data science Artificial Intelligence Machine Learning Computer Vision Software Development
  1. AI needs to learn how to explain its decisions. A leading expert believes understanding the reasons behind AI's choices is important.
  2. Data science is increasingly used in different fields, even fashion. Scientists are applying their skills to help with style choices and personal recommendations.
  3. Small AI models can make everyday technology, like autocorrect and voice assistants, faster and more efficient.

[in case you missed it] Data Science Weekly - Issue 306

Data Science Weekly Newsletter • 0 implied HN points • 06 Oct 19
🕹 Technology AI Data science Machine Learning Software Development Algorithms
  1. Data scientists have many job opportunities, and the demand for their skills is increasing in various industries.
  2. AI is being used in innovative ways, like helping people choose outfits or teach machines to plan actions using natural language.
  3. Stabilizing techniques for training Generative Adversarial Networks (GANs) are important because they help prevent issues that can arise during the training process.

Post-Quantum Cryptography Standards

Quantum Formalism • 0 implied HN points • 05 Jul 22
🕹 Technology Cryptography Courses Community Machine Learning
  1. The US National Institute of Standards and Technology announced post-quantum cryptography standardisation proposals, marking a historic day in modern cryptography.
  2. Cryptography courses will now include post-quantum cryptography standards in the curriculum, with a focus on the selected standards.
  3. The Quantum Formalism community encourages participation in lectures, Discord community engagements, and sponsorships for events like LOGML Summer School, emphasizing the importance of advanced Geometry in Machine Learning.

[in case you missed it] Data Science Weekly - Issue 298

Data Science Weekly Newsletter • 0 implied HN points • 11 Aug 19
🕹 Technology AI Data science Machine Learning Natural Language Software Development
  1. AI is being used in new ways, like apps that can help match people on dates using algorithms.
  2. Natural Language Processing (NLP) is a growing field, and there are new trends and insights coming from conferences around the world.
  3. Data pipelines are crucial for machine learning projects, as they help with data collection and cleaning.

[Mock]Design a URL Shortening service like goo.gl or bit.ly

The ZenMode • 0 implied HN points • 04 Mar 24
🕹 Technology Design System Architecture Security Scaling Database
  1. A URL shortening service converts long URLs into short, unique ones for easy sharing and remembering.
  2. The steps in shortening a URL involve inputting the long URL, generating a unique short URL, storing the mapping, and redirecting users to the original URL.
  3. Designing a URL shortening service includes high scalability, availability, key generation methods, security measures like rate limiting, and handling data growth using tools like distributed databases.

An Optimal Entanglement Distribution Policy for a Quantum Switch

Quantum Formalism • 0 implied HN points • 13 Sep 22
🕹 Technology Quantum Computing
  1. The webinar discusses an optimal strategy for distributing entanglements in a quantum switch, crucial for quantum network applications.
  2. The proposed Max-Weight scheduling policy aims to generate end-to-end entanglements efficiently at the quantum switch.
  3. The speaker, Thirupathaiah Vasantam, has a background in performance modeling and analysis of communication networks with a focus on quantum networking.

[in case you missed it] Data Science Weekly - Issue 279

Data Science Weekly Newsletter • 0 implied HN points • 30 Mar 19
🕹 Technology Artificial Intelligence Machine Learning Data science Software Development Robotics
  1. Three scientists won the Turing Award for their work on neural networks. This award is a big deal in computing, kind of like a Nobel Prize.
  2. Machine learning is being used to create tools that can help doctors focus more on patients instead of taking notes. This could improve healthcare significantly.
  3. There's a new doodling app that uses AI to turn simple sketches into realistic images. This technology could be useful for video games and movies.

New (?) and hip (?)

Links I Would Gchat You If We Were Friends • 0 implied HN points • 10 Dec 21
🕹 Technology Web3 Cryptocurrency Internet Trends Social media Artificial Intelligence
  1. Web3 is a new internet concept aiming to decentralize control through cryptocurrency systems.
  2. Presearch is an example of a Web3 service offering users payments for data and computing power contributions.
  3. Web3 is gaining attention as the potential future of the web, with support from influential figures and tech lobbyists.

Q&A Session Replay on YouTube!

Quantum Formalism • 0 implied HN points • 15 Aug 23
🕹 Technology Quantum Computing
  1. A Q&A session replay is available on YouTube for the Quantum Hardware course by Quantumformalism.
  2. Those interested in the course should apply before August 25th by filling out the application form.
  3. The Zaiku Group is hosting the Quantumformalism course and provides essential information regarding the course and registration.

Gemma Gemma Gemma

Over-Nite Evaluation • 0 implied HN points • 26 Feb 24
🕹 Technology AI Open Source Benchmarking Evaluation Licensing
  1. Licensing agreements for pre-trained models like Gemma might need to find a better balance between protecting owners and encouraging innovation.
  2. Gemma's performance comparisons show it aligns with existing models in specific tasks, but more evaluation beyond familiar benchmarks is necessary.
  3. Gemma's release signifies Google's investment in the open large language model ecosystem, with future emphasis on model safety and hosting services.

Elliptic Curve Cryptography

Quantum Formalism • 0 implied HN points • 29 Nov 23
🕹 Technology Cryptocurrency Cybersecurity Mobile Blockchain Internet of Things
  1. Elliptic Curve Cryptography (ECC) is crucial for secure internet communications like TLS protocols, mobile security, blockchain, and cryptocurrencies.
  2. ECC is efficient and widely utilized in mobile devices for securing transactions and communications due to lower computational power requirements.
  3. ECC plays a significant role in various sectors like government communications, wireless security protocols, and cloud computing due to its high security and efficiency.

Elliptic Curve Cryptography Course + Quantum Tea

Quantum Formalism • 0 implied HN points • 13 Dec 23
🕹 Technology Cryptocurrency
  1. The Elliptic Curve Cryptography course has an upcoming first live lecture scheduled for December 27th, with a strict cap on live attendees to enhance interactivity.
  2. The Quantum Tea open discussion forum started with a free-form session but will introduce more structured discussions exploring alternative viewpoints.
  3. You can register for both the ECC course and Quantum Tea sessions using the provided links to secure your spot.

Coming soon...

Platform Papers • 0 implied HN points • 30 Dec 21
🕹 Technology Research Digital Platforms Big Tech Academic Platform Competition
  1. Platformpapers will start publishing monthly blog posts in 2022 covering the latest academic research on digital platforms and big tech
  2. The posts will summarize and contextualize articles from the platform papers references database to make the research more accessible to a wider audience
  3. The goal is to engage individuals interested in platforms such as scholars, students, managers, creators, and policy makers