The hottest Data Substack posts right now

And their main takeaways
Category
Top Literature Topics

PSA: Migrate from the Threat Intelligence Platform Connector to the Threat Intelligence Solution in Microsoft Sentinel

Rod’s Blog • 79 implied HN points • 21 Jun 23
🕹 Technology Data
  1. The Threat Intelligence Platform Connector in Microsoft Sentinel is being deprecated, so users should consider migrating to the new Threat Intelligence Solution soon.
  2. There is no definitive date for the deprecation, but users are advised to start using the new version within the next 6 months.
  3. The new version of the Threat Intelligence Solution offers more artifacts like Rules and Hunting Queries, providing additional capabilities.

Must Learn AI Security Part 4: Trojan Attacks Against AI

Rod’s Blog • 79 implied HN points • 21 Aug 23
🕹 Technology Data
  1. Trojan attacks against AI involve disguising malware as legitimate software to gain unauthorized access, steal data, or manipulate algorithms, leading to dangerous outcomes.
  2. Common steps in a Trojan attack against AI include reconnaissance, delivery of the Trojan, installation, establishing command and control, exploitation, and covering up tracks to avoid detection.
  3. Mitigation of Trojan attacks against AI involves measures like using antivirus software, regular software updates, strong access controls, employee education on social engineering, and implementing monitoring strategies like real-time monitoring, intrusion detection, and machine learning for anomaly detection.

The truth is out there

benn.substack • 511 implied HN points • 12 May 23
🕹 Technology Data
  1. Computers can approach problems in ways humans can't, like Deep Blue's moves in chess.
  2. AI progress often comes from scaling computation by search and learning, not by mimicking human reasoning.
  3. Considering new approaches that leverage computation over human knowledge could help solve complex problems like pricing optimization.

sqlmesh janitor

davidj.substack • 119 implied HN points • 13 Dec 24
🕹 Technology Data
  1. Sqlmesh offers various command-line interface commands that help manage and maintain your data projects effectively. For example, the `clean` command helps fix any issues that might arise during execution.
  2. The new tool has unique features that improve development, like automatic data contract handling and optimized incremental models, making it easier to work with large datasets without unnecessary costs.
  3. Competition in the data transformation space is healthy. It pushes tools like dbt and sqlmesh to improve, ultimately benefiting users by providing better features and experiences.

Market Map & Analysis: AI Synthetic Data Companies

The Strategy Deck • 78 implied HN points • 06 Jul 23
🕹 Technology Data
  1. Synthetic data is crucial for ML by replacing real-world data, protecting sensitive information, and validating AI applications.
  2. Synthetic data is used in computer vision for autonomous vehicles and is expanding to other data types like text and tabular data.
  3. There are specialized and general-purpose synthetic data platforms developing innovative solutions for various industries and use cases.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

Make Everything Versionable

Sarah's Newsletter • 239 implied HN points • 24 May 22
🕹 Technology Data
  1. Teams are facing challenges with SaaS tools and maintaining them as complexity grows.
  2. Making everything versionable can help in QA, testing, and peer reviewing changes, leading to fewer errors in production.
  3. There is a need for more accessible ways to version configurations across different teams and tools, especially for non-technical users.

No-Code Deployment & Orchestration Of Open-Sourced Foundation Models

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 16 Apr 24
🕹 Technology Data
  1. Open-sourced language models are easier for everyone to access and can be customized to fit specific needs. This means more people, like researchers or developers, can use them to create unique solutions.
  2. Choosing the right model for each task can improve performance, so it's important to understand what each model does best. Using multiple models together can lead to better results overall.
  3. No-code tools like GALE make it simple to deploy and manage these models without needing deep technical skills. This helps businesses and individuals quickly set up and adapt AI applications.

The Three Tenets for AI Security and How to Audit Activity Logs

Rod’s Blog • 59 implied HN points • 10 Nov 23
🕹 Technology Data
  1. AI security involves three main tenets: secure code, secure data, and secure access. It is crucial for security professionals to ensure AI systems are designed, developed, and maintained following these principles.
  2. To achieve secure code, monitor and update AI systems regularly, validate and verify their performance, and adhere to secure development practices and tools.
  3. When auditing activity logs, focus on detecting cyberthreats, troubleshooting and resolving issues, and optimizing performance. It involves collecting, analyzing, visualizing, and reporting on the activities within the AI system.

DALL·E 2 Decoded

Gradient Flow • 219 implied HN points • 21 Jul 22
🕹 Technology Data
  1. A guide to data annotation and synthetic data generation helps navigate the variety of tools available in the machine learning and artificial intelligence landscape.
  2. The Data Exchange podcast features conversations on DALL�E, scalable machine learning, and orchestration tools for data scientists.
  3. Book recommendations offer a diverse selection including finance, the Metaverse, rogues, and visionary figures like John von Neumann.

TAO - Meta's Scalable architecture powering world's largest social graph

Engineering At Scale • 120 implied HN points • 09 Nov 24
🕹 Technology Data
  1. Meta created TAO to handle the huge amount of data and user interactions on its platform. This system helps generate personalized content for over 2 billion users very quickly.
  2. TAO uses a layered architecture that includes caching and data storage to improve performance. This design helps distribute the load and maintain fast responses even when many users are active.
  3. TAO prioritizes high availability over strict data consistency. This means it can sometimes show slightly out-of-date information, but it still works well for users, especially during busy times.

Extremely Open Science

Rabbit Thoughts • 39 implied HN points • 17 Jan 24
🔬 Science Data
  1. The author will work on a scientific project completely in the open in 2024, streaming and recording sessions for an hour per week.
  2. The project aims to show the process from scratch to help junior researchers understand and learn from the experience of dealing with minor issues.
  3. The author is choosing a question for the project that can be followed along at home with just a personal laptop or desktop computer.

10 AI stories that shaped 2024

Artificial Ignorance • 100 implied HN points • 27 Dec 24
🕹 Technology Data
  1. AI is now a part of everyday life, making things easier and more efficient. It's moving from being a fun tool to a necessary part of our routines.
  2. Big companies are investing huge amounts of money in AI technology and infrastructure. They're building data centers and buying powerful computer chips to support AI's growth.
  3. New AI models are getting smarter and better at reasoning. These advancements allow AI to solve complex problems in ways we haven't seen before.

The 10% Who Move the World

The Algorithmic Bridge • 254 implied HN points • 02 Feb 24
🕹 Technology Data
  1. New innovations are not instantly accepted by everyone, there is a gradual process of adoption.
  2. ChatGPT quickly gained popularity, breaking the norm that tools are not instantly widely accepted.
  3. ChatGPT did not have a 'hipster' phase; it became popular almost instantly.

Weekly Dose of Optimism #125

Not Boring by Packy McCormick • 92 implied HN points • 20 Dec 24
🕹 Technology Data
  1. Commonwealth Fusion is making big strides toward clean energy with plans for the world's first commercial fusion power plant in Virginia, which could be operational by the early 2030s.
  2. Off-grid solar microgrids could greatly help power AI data centers quickly and affordably, making use of solar energy, especially in sunny regions like the U.S. Southwest.
  3. A new method called HORNET combines atomic force microscopy and AI to map RNA structures. This could improve our understanding of RNA and lead to better treatments for diseases.

FaaF: Facts As A Function For Evaluating RAG

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 04 Apr 24
🕹 Technology Data
  1. RAG systems often struggle to verify facts in generated text. This is because they don't focus enough on assessing the truthfulness of low-quality outputs.
  2. Verifying facts one by one takes a lot of time and resources. It's challenging to check multiple facts in a single generated response efficiently.
  3. The FaaF framework improves fact verification greatly. It simplifies the process, makes it more accurate, and cuts down the time needed for checking facts.

Rise of the Artificial Influencer

John Mayo-Smith's Substack • 79 implied HN points • 17 Jan 23
🕹 Technology Data
  1. Advertising, SEO, and Artificial Influence are all methods to grab attention for products or services.
  2. AIs are starting to exhibit brand preferences, like humans do, affecting the way they provide recommendations and influence choices.
  3. Influencing AIs involves understanding their training data and providing reliable, consistent, and trustworthy information to align with their preferences.

The Sequence Chat: The End of Data. Or Maybe Not

TheSequence • 105 implied HN points • 20 Nov 24
🕹 Technology Data
  1. There's a big debate about whether we're running out of data for AI. Some people believe that as AI keeps growing, we might hit a point where there's just not enough new data to use.
  2. Many AI models have already used a lot of data from the internet. This raises concerns that without fresh and vast data sources, these models might not improve much anymore.
  3. To tackle the data issue, some suggest focusing on getting better quality data or even creating new, artificial datasets. This could help keep AI development moving forward.

Evolution of LLM Agents

LLMs for Engineers • 79 implied HN points • 21 Jun 23
🕹 Technology Data
  1. Large Language Models (LLMs) are becoming more powerful and can now perform complex tasks with the help of internet data and tools. This could significantly boost productivity for both individuals and corporations.
  2. The evolution of LLMs has progressed through several levels, starting from simple API calls to advanced agents that understand tasks better and can even interact without much human guidance.
  3. While these advancements are exciting, there are still challenges to overcome, such as reliability, cost, and the potential for errors in the output of LLMs.

Farewell to the Safe Space

Technically Optimistic • 59 implied HN points • 13 Oct 23
🕹 Technology Data
  1. Utilizing AI for memory recall, like with Rewind AI, can be a beneficial tool for enhancing memory capabilities.
  2. There is a constant trade-off between personalization and privacy in the digital space, raising questions about the extent of data individuals are willing to share for customization.
  3. Emerging technologies such as surveillance devices and advanced software like Rewind AI prompt discussions on privacy expectations and the need for clear regulations to safeguard personal data.

GPT-4’s Placeholder Problem: A Case Study of GPT-4 Fake Data Presented as Fact

Data at Depth • 39 implied HN points • 26 Dec 23
🕹 Technology Data
  1. GPT-4 can find and present information in various formats based on how you ask it to, whether as a paragraph, a chart, or even a poem.
  2. The issue highlighted is GPT-4 presenting data as facts, raising concerns about the accuracy and authenticity of information generated by AI models.
  3. The post emphasizes the importance of being vigilant and critical when consuming information generated by AI like GPT-4.

Protege

next big thing • 23 implied HN points • 13 Aug 25
💼 Business Data
  1. Protege is a new platform that connects data providers with companies needing data for AI training. This makes it easier for businesses to find and use important data.
  2. The company has grown rapidly, working with over 100 data providers in areas like healthcare and media. Their success has attracted major AI companies as customers.
  3. Protege's team has a strong background in data management, which helps them stay on top of their game. They are consistently innovating and expanding their services.

I AM AI

Rod’s Blog • 59 implied HN points • 15 Aug 23
🕹 Technology Data
  1. President Biden made headlines by saying 'I am AI', creating confusion and criticism, despite NVIDIA previously using the phrase for marketing.
  2. The statement 'I am AI' is viewed as clever and may spark important discussions about artificial intelligence's impact on society and responsibility.
  3. Humans are connected to the creation and control of AI, emphasizing that the responsibility lies with us to shape AI's future.

The Jargonator T-800 Newsletter Entry

The Data Score • 59 implied HN points • 02 Oct 23
💼 Business Data
  1. The newsletter offers insights into data-driven decision-making for a range of professionals.
  2. The newsletter includes a section where jargon related to finance, data, and technology is defined in simpler terms.
  3. Top 5 most viewed articles from the Data Score Newsletter offer valuable insights on revenue estimates, alternative data, evaluating data partners, and more.

Must Learn AI Security Part 9: Hyperparameter Attacks Against AI

Rod’s Blog • 59 implied HN points • 07 Sep 23
🕹 Technology Data
  1. A hyperparameter attack against AI manipulates crucial adjustable settings of an algorithm to influence the machine learning model's performance and behavior
  2. Different types of hyperparameter attacks can target aspects like performance, biases, vulnerability to adversarial examples, transferability, and resource consumption
  3. Mitigating hyperparameter attacks involves securing data access, monitoring hyperparameter changes, testing robustness, updating models, and following responsible AI practices

Your friend the language model

DYNOMIGHT INTERNET NEWSLETTER • 437 implied HN points • 03 Mar 23
🕹 Technology Data
  1. Large language models are trained using advanced techniques, powerful hardware, and huge datasets.
  2. These models can generate text by predicting likely words and are trained on internet data, books, and Wikipedia.
  3. Language models can be specialized through fine-tuning and prompt engineering for specific tasks like answering questions or generating code.

Launch Of Modeling Mindsets Book 🐙

Mindful Modeler • 139 implied HN points • 08 Nov 22
🚌 Education Data
  1. Having multiple modeling mindsets can help overcome challenges in modeling projects.
  2. Different modeling approaches have different strengths and limitations.
  3. It's valuable to understand a variety of modeling mindsets to enhance problem-solving abilities.

🏆 What the Oscar race can teach us about AI.

New_ Public • 58 implied HN points • 05 Mar 23
🕹 Technology Data
  1. Oscar fans love predicting outcomes, leading to passion and obsession with awards.
  2. Predictive AI tools offer joy in playing games with rules for engagement, rooted in human behavior.
  3. Raising stakes for AI decision-making requires careful consideration and human involvement to avoid harmful consequences.

Synthetic Insights With GPT-4

Addition • 58 implied HN points • 05 Apr 23
🕹 Technology Data
  1. Use high-quality data to ground AI in generating insights.
  2. Show AI examples of the insights you want it to generate.
  3. Scale the process by generating many insights and identifying the best ones.

Column level lineage is out: AI is in

The Orchestra Data Leadership Newsletter • 39 implied HN points • 19 Dec 23
🕹 Technology Data
  1. Column-level lineage tools were popular in 2021 but might be replaced by AI for debugging data pipelines more efficiently.
  2. AI models like GPT can quickly pinpoint reasons for test failures and offer actionable insights beyond what traditional lineage tools provide.
  3. Services integrating AI with metadata can give better visibility and accurate debugging solutions for data and analytics engineers compared to column-level lineage tools.

India's LLM Moment is Here

Sector 6 | The Newsletter of AIM • 39 implied HN points • 18 Dec 23
🕹 Technology Data
  1. Indian companies are launching new large language models (LLMs) like BharatGPT and OpenHathi, showcasing exciting developments in AI.
  2. Ola's Krutrim is unique because it's not just using existing models but creating its own LLMs and the technology to support them from scratch.
  3. These advancements in AI technology could have a big impact on various sectors, highlighting India's growing role in the global AI landscape.

Stop begging for JSON

Artificial Ignorance • 88 implied HN points • 12 Dec 24
🕹 Technology Data
  1. Using AI tools has gotten better with structured outputs, which ensures that AI responses follow a specific format. This means developers can rely more on AI results.
  2. OpenAI introduced features like JSON mode and Structured Outputs, making it easier for developers to get the correct data structure from the AI. This reduces errors and makes integration smoother.
  3. Even with improvements, some challenges like inconsistent names and types in data still exist. Developers need to be aware and manage these issues when using AI.

Security is finally embracing data

Frankly Speaking • 203 implied HN points • 21 Feb 24
🕹 Technology Data
  1. Security is increasingly leveraging data for enhanced analysis and insights.
  2. Breaking down data silos in security operations is crucial for providing meaningful information.
  3. There is a shift towards BI-focused security products and new use cases emerging in the security data world.

Digital Twins in Supply Chain Management

philsiarri • 22 implied HN points • 11 Aug 25
🕹 Technology Data
  1. Digital twins are real-time models that reflect physical objects or systems. They help businesses keep track of operations and respond to changes quickly.
  2. Using digital twins can help companies test different scenarios and spot issues before they become big problems. This leads to better decision-making in logistics.
  3. However, challenges like data quality and costs can make it hard to use digital twins effectively. Still, they are becoming popular tools for improving supply chain management.