The hottest AI Substack posts right now

And their main takeaways
Category
Top Technology Topics

Prompt engineering is spaghetti code

Sunday Letters • 59 implied HN points • 08 Oct 23
🕹 Technology AI
  1. Prompt engineering is not a lasting software discipline; it may fade away as technology improves. It's a reaction to a lack of computing resources, trying to make every use of AI efficient.
  2. Using AI tools should be approached like programming: break tasks into smaller pieces to handle them better. This is more effective than creating complex prompts that are hard to manage.
  3. It's better to focus on making something work well before worrying about cost or optimization. Don't stress about minimizing resource use until the solution is working reliably.

Must Learn AI Security Compendium 10: Challenges of Enhancing AI Language Models with External Knowledge

Rod’s Blog • 59 implied HN points • 12 Oct 23
🕹 Technology AI
  1. Retrieval-Augmented Generation (RAG) enhances AI language models by combining them with external knowledge sources, improving the quality and accuracy of generated responses.
  2. RAG offers benefits such as access to current information, increased contextual understanding, and reduced risk of incorrect data, but it also comes with challenges like data integration and semantic relevance.
  3. The future of RAG includes developments like fine-grained relevance ranking, domain-specific knowledge bases, real-time updates, and ethical considerations to ensure responsible use.

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 AI
  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.

Edge 458: From Pre-training to Post-training. Inside the Amazing Tülu 3 Framework

TheSequence • 91 implied HN points • 19 Dec 24
🕹 Technology AI
  1. There is a new focus in AI from pre-training models to post-training methods. This change is happening because it's now easier to train models with data from the internet.
  2. The Tülu 3 framework is designed to improve existing language models after their initial training. It highlights how important the post-training process is for making models work better.
  3. By making post-training techniques more open and accessible, Tülu 3 aims to help the open-source community compete with top-performing private models.

OpenAI’s Sora for video, Gemini 1.5's infinite context, and a secret Mistral model

Democratizing Automation • 221 implied HN points • 16 Feb 24
🕹 Technology AI
  1. OpenAI introduced Sora, an impressive video generation model blending Vision Transformer and diffusion model techniques
  2. Google unveiled Gemini 1.5 Pro with nearly infinite context length, advancing the performance and efficiency using the Mixture of Expert as the base architecture
  3. The emergence of Mistral-Next model in the ChatBot Arena hints at an upcoming release, showing promising test results and setting expectations as a potential competitor to GPT4
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Protege

next big thing • 23 implied HN points • 13 Aug 25
💼 Business AI
  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.

The Silent Infrastructure Behind AI: Why Vector Databases Are Booming

philsiarri • 22 implied HN points • 21 Aug 25
🕹 Technology AI
  1. Vector databases store information in a way that captures meaning, helping AI search for similarities instead of exact matches. This means a sentence or an image can be turned into a special numeric form that AI understands better.
  2. Traditional databases are good for exact searches but struggle with the complex needs of AI. Vector databases are designed for quick and efficient searches involving high-dimensional data, making them much better for AI applications.
  3. Many companies like Pinecone and Weaviate are leading the way in vector databases, which are being used in various areas like e-commerce, fraud detection, and customer support to improve how we find and use information.

I AM AI

Rod’s Blog • 59 implied HN points • 15 Aug 23
🕹 Technology AI
  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.

Using Azure AI Studio to Reduce Hallucinations

Rod’s Blog • 59 implied HN points • 08 Aug 23
🕹 Technology AI
  1. Hallucinations in AI can lead to unpredictable and incorrect responses.
  2. Azure AI Studio offers tools like adjusting Temperature and Top P to mitigate hallucinations.
  3. Continuous monitoring and configuration tuning are crucial to prevent attacks like Prompt Injection and Data Poisoning.

Must Learn AI Security Compendium 6: Ensuring Trust and Ethical Practices

Rod’s Blog • 59 implied HN points • 26 Sep 23
🕹 Technology AI
  1. Responsible AI requires prioritizing ethical practices to avoid risks and gain trust from users and stakeholders.
  2. Irresponsible AI practices can lead to unfair bias, lack of transparency, privacy concerns, and negative social impacts.
  3. Organizations can implement responsible AI by prioritizing human-centeredness, fairness, transparency, privacy, accountability, continuous monitoring, and collaborative engagement.

Must Learn AI Security Compendium 3: Exploring the Different Types of AI Technology

Rod’s Blog • 59 implied HN points • 12 Sep 23
🕹 Technology AI
  1. AI can be categorized into Narrow AI, General AI, and Super AI based on capabilities, each with different levels of human-like intelligence.
  2. AI can also be classified based on functionality into Reactive Machines, Limited Memory, Theory of Mind, and Self-awareness, each with unique ways of processing information and interacting with the environment.
  3. Applications of AI in various industries like healthcare, finance, transportation, and retail are transforming decision-making, efficiency, and innovation, but ethical considerations and challenges like data quality and interpretability must be addressed for responsible AI development.

Call for Writing: Models for Making Distance.

Cybernetic Forests • 59 implied HN points • 27 Sep 23
🎨 Art & Illustration AI
  1. The call for writing is about seeking contributions for a print zine called Models for Making Distance.
  2. Contributions could include manifestos, art instructions, performances, literary works, and propaganda that explore distancing from algorithmic order.
  3. The project is organized by the Algorithmic Resistance Research Group, a collective focused on critical exploration and creative resistance to algorithmic culture.

Must Learn AI Security Compendium 5: The Rise of AI in the IT Sector

Rod’s Blog • 59 implied HN points • 20 Sep 23
🕹 Technology AI
  1. Artificial Intelligence is revolutionizing the IT sector, with the rise of models like ChatGPT expanding its potential applications.
  2. AI enhances productivity by speeding up tasks that would otherwise take hours, like code generation using PowerShell scripting with generative AI.
  3. AI fosters creativity and innovation, such as in content creation and marketing, and requires ethical considerations for responsible development.

Language is a SimCity

Cybernetic Forests • 59 implied HN points • 02 Jul 23
🔬 Science AI
  1. Language can be seen as a dynamic city, shaped by collective contributions that form its intricate structure.
  2. Generative AI models, like GPT4, rely on statistics and random selection to produce text, often betraying a lack of true understanding.
  3. Human communication involves a choice between shallow, statistically-driven speech, like that of machines, and deeper, intent-driven speech that seeks to convey personal truths.

Must Learn AI Security Compendium 2: Generative AI vs. Machine Learning

Rod’s Blog • 59 implied HN points • 11 Sep 23
🕹 Technology AI
  1. Machine learning empowers computers to learn from data without explicit programming, helping them make predictions and decisions.
  2. Generative AI focuses on creating new data based on training data, emphasizing creativity and innovation.
  3. Both machine learning and generative AI have unique applications - from fraud detection and image recognition in machine learning to image generation and music composition in generative AI.

Address Not Found (Part 2)

Cybernetic Forests • 59 implied HN points • 18 Jun 23
🕹 Technology AI
  1. Communication technologies historically categorized into one-to-one, one-to-many, and many-to-many transmission systems.
  2. Artificial Intelligence operates in a unique structure called many-to-one-to-one, where data from multiple sources shapes responses for individual users.
  3. AI systems, despite the appearance of one-to-one engagement, actually function asynchronously and as a blend of many-to-one transmission, controlled by the operators and designers.

Tip: Reset Your Wrecked Web App from the Azure OpenAI Chat Playground

Rod’s Blog • 59 implied HN points • 30 Jun 23
🕹 Technology AI
  1. You can reset your web app using Azure OpenAI Studio, which is helpful when you mess something up and need to start fresh.
  2. This feature is typically used to update apps with new models, but it can also be handy for reverting back to a clean slate to try again.
  3. By deploying your existing web app through the 'Deploy to' button, you can effectively reset it to its initial state.

Must Learn AI Security Part 9: Hyperparameter Attacks Against AI

Rod’s Blog • 59 implied HN points • 07 Sep 23
🕹 Technology AI
  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

Is ChatGPT Getting worse? A Case Study on Confirmation Bias

The Data Score • 59 implied HN points • 20 Jul 23
🕹 Technology AI
  1. Testing and improving AI models, like ChatGPT, is crucial as our reliance on AI grows. Ensuring model performance and explainability is key for professionals in the field.
  2. Machine learning and AI models face challenges with explainability, especially in the context of large language models like ChatGPT. Specific wording and temperature settings can greatly impact model outputs.
  3. Confirmation bias is a common human tendency to search for and interpret information that aligns with existing beliefs. It's important to recognize and manage biases when assessing AI model performance.

Made by AI: A Modern Monty Python Skit Sketch

Rod’s Blog • 59 implied HN points • 25 Jul 23
😂 Humor AI
  1. The skit humorously portrays a group of Monty Python members as trendy influencers struggling to gain social media followers, with a twist involving a rubber chicken symbolizing happiness and enlightenment.
  2. The story emphasizes the absurdity of life and the importance of not taking oneself too seriously in the pursuit of happiness.
  3. Creating AI-generated skits can lead to unique and entertaining content, offering a fun way to explore creativity and humor.

Writing as synthesis

imperfect offerings • 59 implied HN points • 01 Oct 23
🕹 Technology AI
  1. Generative AI is being regulated in industries like Hollywood to ensure human writers receive proper credit and compensation even when AI-generated content is used in the development process.
  2. The future of AI in education presents opportunities for collaborative efforts to create public sector language models, potentially shifting costs to governments for developing foundational models for various languages.
  3. Vygotsky's perspective emphasizes how generative AI tools should engage humans in advanced thought processes and interpersonal activities, rather than just producing text, sparking questions about learners' interactions and collective knowledge production.

Microsoft Sentinel SOC 101: How to Detect and Mitigate Keylogger Attacks with Microsoft Sentinel

Rod’s Blog • 59 implied HN points • 02 Oct 23
🕹 Technology AI
  1. Keyloggers are commonly used by cybercriminals to steal sensitive data, so it's crucial for organizations to detect and mitigate keylogger attacks to safeguard their information and finances.
  2. Microsoft Sentinel, a cloud-native SIEM system, can help in detecting keylogger attacks by collecting logs from endpoints, analyzing them using advanced analytics, and providing tools to investigate alerts and respond to threats.
  3. To mitigate keylogger attacks, organizations can implement multi-factor authentication, educate users about keylogger risks, and utilize endpoint protection software like Microsoft Defender for Endpoint.

Using the Rabin Karp Algorithm to speed up your code[Technique Tuesdays]

Technology Made Simple • 59 implied HN points • 19 Apr 23
🕹 Technology AI
  1. The Rabin Karp algorithm is a string-searching technique that uses hashing to efficiently find patterns in texts.
  2. It is useful for tasks like detecting plagiarism, finding keywords, or searching for DNA sequences in large texts.
  3. The algorithm works by calculating hash values at each position of the text, making it faster than naive string-matching algorithms.

How much of our disbelief can we suspend in augmented reality?

On Looking • 59 implied HN points • 27 Jun 23
🕹 Technology AI
  1. Technologies like augmented reality challenge our perception and reshape our senses, training us to suspend disbelief and engaging us in a new form of visual literacy.
  2. The labor of making things look real involves an intricate mix of technology, cultural references, and societal norms, often blurring the lines between what is real and what is constructed.
  3. The desire for connection in an increasingly technological world raises questions about the authenticity of human interactions and challenges us to navigate the fine line between presence and absence, between virtual and physical realms.

Monitoring ChatGPT Usage in Microsoft Sentinel

Rod’s Blog • 59 implied HN points • 08 Mar 23
🕹 Technology AI
  1. Monitoring ChatGPT in Microsoft Sentinel involves ensuring secure and responsible AI usage
  2. Utilizing detection rules like Watchlists can help monitor and secure ChatGPT API usage
  3. Open-sourcing resources like KQL queries and rules aids in managing AI monitoring challenges

Censorship’s Impact on China’s Chatbots

ChinaTalk • 207 implied HN points • 11 Mar 24
🕹 Technology AI
  1. Chinese AI chatbots are subject to strict censorship by the Cyberspace Administration of China, affecting their responses to political questions.
  2. There is a noticeable tradeoff between content control and value alignment in Chinese chatbots, highlighting a balance between censorship and quality of output.
  3. Censorship in Chinese chatbots involves value alignment training and keyword filtering, showing how Chinese regulators influence the responses of AI models to favor Beijing's values.

Your friend the language model

DYNOMIGHT INTERNET NEWSLETTER • 437 implied HN points • 03 Mar 23
🕹 Technology AI
  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.

The state of B2B contracts in 2024

Kyle Poyar’s Growth Unhinged • 228 implied HN points • 07 Feb 24
💼 Business AI
  1. Key stats on B2B software contracts include negotiation tips and common terms to expect.
  2. There has been a significant increase in AI-related clauses in B2B contracts.
  3. In B2B contracts, automatic fee increases are common, particularly with the larger enterprise customers.

I am an LLM and I am writing this a word at a time

70 Years Old. WTF! • 58 implied HN points • 19 Feb 23
🕹 Technology AI
  1. The author explains what an LLM, or Large Language Model, is - a system that predicts the next word in a sequence.
  2. The author discusses the process of writing and editing as an LLM, revealing similarities with ChatGPT and human writers.
  3. The author reflects on the collaboration between themselves and technology like ChatGPT in the writing process, highlighting the potential of human-machine partnerships in creativity.

The dread of ChatGPT

Digital Epidemiology • 58 implied HN points • 15 Feb 23
🕹 Technology AI
  1. Feeling dread about AI is common, even among those close to technology.
  2. Technology revolutions follow predictable patterns of early failures and eventual mass adoption.
  3. The speed of AI development is a key concern, potentially leading to irreversible damage and shifts in power dynamics.

LLMs are machines. Are you one too?

70 Years Old. WTF! • 58 implied HN points • 19 Feb 23
🕹 Technology AI
  1. LLMs are Large Language Models, which are computer systems trained to generate language based on patterns.
  2. LLMs can write better than most humans, but they lack the freedom of expression that humans have.
  3. The difference between how a human writes and how a machine like ChatGPT generates text is the ability to freely use explicit language.

💬 Elon Musk Is on ChatGPT's Good Side

aidaily • 58 implied HN points • 21 Feb 23
🕹 Technology AI
  1. AI search engines like ChatGPT are changing how we access information
  2. The rise of AI chatbots like ChatGPT could lead to more AI bots online
  3. ChatGPT technology has various applications beyond basic internet interactions