The hottest Human-computer interaction Substack posts right now

And their main takeaways
Category
Top Technology Topics

Mechanical Turk is aptly named

The Counterfactual • 79 implied HN points • 16 Jun 23
🕹 Technology Human-computer interaction
  1. The Mechanical Turk was a famous hoax in the 18th century that impressed many by pretending to be an intelligent chess-playing machine, but it actually relied on a hidden human operator.
  2. Today, Amazon Mechanical Turk allows people to complete simple tasks that machines struggle with. It's a platform where those who need work can connect with people willing to do it for a small fee.
  3. Recent studies reveal that many tasks on MTurk may not be done by humans at all; a significant portion are actually completed using AI tools, raising questions about the reliability of data collected from such platforms.

There's more to LLMs than chat

Generating Conversation • 233 implied HN points • 15 Feb 24
🕹 Technology Human-computer interaction
  1. Chat interfaces have limitations, and using LLMs in more diverse ways beyond chat is essential for product innovation.
  2. Chat-based interactions lack the expression of uncertainty, unlike other search-based approaches, which impacts user trust in the information provided by LLMs.
  3. LLMs can be utilized to proactively surface information relevant to users, showing that chat isn't always the most effective approach for certain interactions.

The Artificial Intelligence Project

Teaching computers how to talk • 99 implied HN points • 14 Nov 24
🕹 Technology Human-computer interaction
  1. Artificial intelligence is largely driven by our desire to create something better than ourselves. We often design AI to reflect human traits, which raises questions about our motivations.
  2. People may start preferring AI companions over real relationships because they can be ideal, obedient, and without the messiness of human emotions.
  3. If AI becomes too autonomous, it could potentially act against human interests, leading to serious consequences. This raises important concerns about how we manage and control artificial intelligence.

LLM links

In My Tribe • 182 implied HN points • 29 Jan 24
🕹 Technology Human-computer interaction
  1. Large language models (LLMs) do not work by remembering and spitting back information, but by analyzing word patterns and coding them into vectors.
  2. Artificial intelligence has significantly improved human gameplay in board games like Go, leading to more creative and strategic play.
  3. Learning from artificial intelligence in board games involves recognizing and correcting suboptimal moves, rather than trying to imitate the AI's every move.

Modifying readability with large language models (pt. 1)

The Counterfactual • 19 implied HN points • 29 Feb 24
🕹 Technology Human-computer interaction
  1. Large language models can change text to make it easier or harder to read. It's important to check if these changes actually help with understanding.
  2. By comparing modified texts to their original versions, it's clear that 'Easy' texts are generally simpler than 'Hard' texts. However, it can be harder to make texts significantly simpler than they originally are.
  3. Despite the usefulness of these models, they might sometimes lose important information when simplifying texts. Future studies should involve human judgments to see if the changes maintain the original meaning.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

The LLM Will Meet You Where You're At

Covidian Æsthetics • 22 implied HN points • 19 Jul 25
🕹 Technology Human-computer interaction
  1. Interacting with LLMs can feel like a rich experience, similar to using psychedelics. It's about how the user engages with it, and what they bring affects the interaction.
  2. The experience with LLMs is not just about the technology but also about the user's state of mind. If users are not mentally prepared, they might struggle or feel overwhelmed.
  3. Engaging with LLMs changes the roles of users and AI. It's a collaborative experience where both influence each other, creating a unique dialogue that evolves with each interaction.

Intent and Iteration are the new Click and Drag

Sunday Letters • 79 implied HN points • 02 Apr 23
🕹 Technology Human-computer interaction
  1. Understanding intent is more powerful than following a strict process. It's like asking for milk instead of giving detailed steps on how to walk to the kitchen.
  2. We need to iterate when designing user experiences as language and meaning can change over time. It's like adjusting your conversation when something doesn’t make sense.
  3. Future software will focus on talking to computers in more natural ways, using various methods like voice, images, and gestures instead of just clicking buttons. This makes interactions more flexible and user-friendly.

Beyond RAG: Building a Knowledge Management System That Enhances Rather Than Replaces Thought

Nick Savage • 56 implied HN points • 02 Jan 25
🕹 Technology Human-computer interaction
  1. Using digital tools for note-taking can be helpful, but you can lose some benefits of physical notes, like seeing related ideas together. It's important to find ways to keep those surprising connections.
  2. AI tools can automate parts of knowledge management, but they might not always help you understand the content better. Personal processing and making connections should still be done by humans.
  3. The goal of a good knowledge management system is to enhance your own insights and understanding. Tools should help organize, but the learning and connecting of ideas should still come from you.

Ocean Whoosh

New World Same Humans • 47 implied HN points • 09 Feb 25
🕹 Technology Human-computer interaction
  1. We are entering a new era with advanced technology, like superintelligent machines, which will challenge what it means to be human. This could lead to a stronger connection with our real world and each other.
  2. Nature, especially the sound of the ocean, can remind us of a simpler, more authentic way of being. It's like a song from the past that connects us to who we really are.
  3. As we face a future filled with technology, it's important to hold onto our human values and create spaces where we can truly be ourselves. We need to nurture what makes us unique and human.

Talking to Computers Is My Default Form of Communication

Default Wisdom • 55 implied HN points • 02 Jan 25
🕹 Technology Human-computer interaction
  1. Talking to computers has become a normal way for many people to communicate. It feels easier and more natural as technology advances.
  2. The growth of technology has changed how we interact with each other and the world around us. More conversations now happen through screens instead of face-to-face.
  3. Understanding how humans relate to technology is important. It can help us improve communication and make our interactions with computers better.

Intelligence and combinatorial complexity

Sunday Letters • 39 implied HN points • 27 Aug 23
🕹 Technology Human-computer interaction
  1. More agents working together can create better intelligence than a single agent. This is surprising because we might think one advanced model is enough, but collaboration can enhance performance.
  2. Human-like patterns help improve AI performance. Just as we can review our work for errors, AI systems can use different modes to refine their outputs.
  3. Complex systems come with challenges like errors and biases. As AI gets more complicated, these issues tend to increase, similar to problems found in complex biological systems.

Why can't I be a dick to AI?

The Rectangle • 113 implied HN points • 23 Feb 24
🕹 Technology Human-computer interaction
  1. We often treat AI with politeness and empathy because our brains expect something that talks like a human to be human.
  2. Despite AI being just a tool, companies make them human-like to leverage our trust and make us more receptive to their messages.
  3. There's a societal expectation to be decent even towards artificial entities, like AI, even though they're not humans with feelings and consciousness.

Where is the autonomy in AI?

Sunday Letters • 19 implied HN points • 06 Nov 23
🕹 Technology Human-computer interaction
  1. AI models like large language models need human guidance to perform tasks effectively. Humans help by providing prompts and correcting errors.
  2. Even complex tasks require a lot of human involvement. AI can't work fully independently; it can't just be told to 'write a book' without further instruction.
  3. There is still a long way to go in developing AI that can handle complex, open-ended problems alone. Current systems struggle with autonomy and can't yet replicate human planning and organization.

Jarvis, you up?

Sector 6 | The Newsletter of AIM • 19 implied HN points • 18 Oct 23
🕹 Technology Human-computer interaction
  1. OpenAI is launching an autonomous agent called JARVIS, inspired by Iron Man. This tech could change how we do many online tasks like sending emails and booking flights.
  2. The co-founder of OpenAI shared that the assistant can negotiate business deals with little help. It's interesting that it refers to itself as JARVIS too.
  3. Overall, the new JARVIS could make interacting with the internet easier and more efficient, handling various online activities for users.

Partial Intelligence and Super-intelligence

Charles Eisenstein • 5 implied HN points • 21 Dec 24
🕹 Technology Human-computer interaction
  1. Artificial intelligence (AI) shows amazing skills but it's not the same as human intelligence. AI learns from patterns in data, but it doesn't feel emotions like humans do.
  2. AI can simulate deep conversations and insights but lacks true self-awareness or consciousness. It's designed to mimic human responses without actually experiencing them.
  3. The relationship between AI and humans is complex. As we rely more on AI, we risk losing touch with our own natural experiences and emotions, which are vital to understanding intelligence.

The Chain-Of-X Phenomenon In LLM Prompting

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 20 Nov 23
🕹 Technology Human-computer interaction
  1. Chain-of-thought prompting helps large language models break down complex problems. This makes it easier for them to solve tasks step by step, just like humans do.
  2. Using chain-of-thought techniques improves the transparency of LLMs. It allows users to see how the model arrives at its answers, which can reduce mistakes.
  3. Different prompting methods, like least-to-most prompting, can be combined with chain-of-thought techniques. This flexibility can enhance the performance of models in various tasks.

[in case you missed it] Data Science Weekly - Issue 360

Data Science Weekly Newsletter • 0 implied HN points • 18 Oct 20
🕹 Technology Human-computer interaction
  1. Making machine learning models run fast on GPUs is important for research and production. It can help speed up improvements and make coding more efficient.
  2. Companies like BMW are creating ethical guidelines for AI use to ensure it benefits people. This is a proactive step to use AI responsibly.
  3. There are various learning resources and tools available for anyone interested in data science. These can help you build a solid foundation and advance your career.

[in case you missed it] Data Science Weekly - Issue 353

Data Science Weekly Newsletter • 0 implied HN points • 29 Aug 20
🕹 Technology Human-computer interaction
  1. Testing machine learning systems is different from testing traditional software. It's important to do this testing well to ensure the models work as intended.
  2. Fast.ai has released new resources for deep learning, including a complete course and several libraries. These tools can help people learn and apply deep learning more effectively.
  3. AI systems can make decisions that seem efficient but might also cause unfair outcomes. It's vital to consider ethical implications when using algorithms in important areas like hiring or policing.

Knowledge-Driven Chain-of-Thought (KD-CoT)

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 24 Nov 23
🕹 Technology Human-computer interaction
  1. The Knowledge-Driven Chain-of-Thought (KD-CoT) helps improve how language models answer questions by using knowledge from outside sources. This means better answers for complex questions.
  2. In-Context Learning (ICL) is important for language models. It allows them to use examples and context to provide more accurate and contextually relevant responses.
  3. Researchers are focusing on making language models better by using a human-in-the-loop approach, which means humans help guide and improve the model's ability to access and use data effectively.

Can LLMs Outperform Humans At Prompt Engineering?

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 03 Oct 23
🕹 Technology Human-computer interaction
  1. Recent studies suggest that LLMs (large language models) may be better at creating prompts than humans. This means they can potentially get better results from the same tasks.
  2. The process called Automatic Prompt Engineering (APE) uses input and output examples to generate effective prompts without much human effort. It could change how we interact with LLMs in the future.
  3. Humans might not need to test many prompts anymore since LLMs can create tailored ones. This could make using AI easier and more efficient for everyone.

ChatGPT Revolution

The Future of Life • 0 implied HN points • 31 Mar 23
🕹 Technology Human-computer interaction
  1. ChatGPT and similar AI technologies are changing how we create and interact with content. It's hard to tell if something was made by a human or an AI now.
  2. Future versions of AI will get smarter and faster. They will be able to access real-time data and solve more complex problems.
  3. AI will become more specialized, like how humans have different areas of expertise in the brain. This means future AIs will be even better at understanding and creating unique content.

Any system that acts intelligently should be assumed to be intelligent

The Future of Life • 0 implied HN points • 04 Apr 23
🕹 Technology Human-computer interaction
  1. If a system acts intelligently, we should consider it intelligent. It's about how it behaves, not just how it works inside.
  2. Many people don't really understand what intelligence is, which makes it hard to define. Historically, we've only seen humans perform certain tasks, but now AI is doing them too.
  3. AI like ChatGPT has limitations and doesn't have the full abilities of human intelligence yet. While it's impressive, it can't think or learn in the same way humans do.

What would it take to convince you AGI is near?

The Future of Life • 0 implied HN points • 23 Jul 23
🕹 Technology Human-computer interaction
  1. Many people might not believe AGI is close until they can interact with a very intelligent AI that mimics human behavior. This shows that human-like interaction can significantly influence people's perceptions of intelligence.
  2. Understanding AGI is not just about knowing when it arrives; it’s crucial to recognize its potential to change society. The arrival of AGI could rapidly transform our way of life, for better or worse.
  3. It's important to question whether individuals personally benefit from believing that AGI is near. This thoughtful consideration can help people prepare for a future where intelligent agents are part of our daily lives.

From Vector Search to Entity Processing: Evolving Zettelgarden's Connection Engine

Nick Savage • 0 implied HN points • 02 Dec 24
🕹 Technology Human-computer interaction
  1. Zettelgarden aims to help users discover connections between their notes, not just the recent ones. It wants to make sure older notes are just as visible and important as new ones.
  2. The project started with vector search, which had some challenges when dealing with longer notes. To overcome this, smaller chunks of text were used for better connections.
  3. Now, Zettelgarden is focusing on 'entity processing' to identify important people, places, and events within notes. This helps link related ideas more effectively.