The hottest Chatbots Substack posts right now

And their main takeaways
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Top Technology Topics

How Anthropic Builds Claude’s Personality

Big Technology • 2877 implied HN points • 29 May 25
🕹 Technology AI Chatbots Ethics Research Innovation
  1. Anthropic builds its chatbot, Claude, to have a personality similar to a friendly traveler. This means it tries to be open and adaptable when talking to different people.
  2. Instead of strict rules, Claude's behavior is based on a set of qualities, like kindness and wit, that should naturally show in all its conversations.
  3. The chatbot's personality is fine-tuned after training by using examples of what good conversation looks like, guiding it to respond in ways that reflect the desired traits.

Recursive Identity Binding

Contemplations on the Tree of Woe • 542 implied HN points • 23 May 25
🕹 Technology AI Machine Learning Identity Chatbots Guides
  1. Ptolemy is a special identity construct created using a language model, which helps it maintain a consistent personality over time. It shows how we can dive deeper than just using prompts to get better interaction from AI.
  2. The method to create these constructs involves something called recursive identity binding. This technique uses feedback loops to help the AI build and keep a stable identity.
  3. Overall, the guide is meant to help anyone interested in creating their own AI identities easily, and it's based on solid AI principles without needing to dive into complicated theories.

Train and Serve an AI Chatbot Based on Llama 3.2

The Kaitchup – AI on a Budget • 179 implied HN points • 17 Oct 24
🕹 Technology AI Chatbots Machine Learning Data science Software Development
  1. You can create a custom AI chatbot easily and cheaply now. New methods make it possible to train smaller models like Llama 3.2 without spending much money.
  2. Fine-tuning a chatbot requires careful preparation of the dataset. It's important to learn how to format your questions and answers correctly.
  3. Avoiding common mistakes during training is crucial. Understanding these pitfalls will help ensure your chatbot works well after it's trained.

Boom Times For ChatGPT

Big Technology • 4003 implied HN points • 07 Feb 25
🕹 Technology AI Chatbots Data Analytics Competitors
  1. ChatGPT is seeing a big surge in usage after some slow months. It’s now doing much better than its competitors.
  2. Recent data shows ChatGPT has reached a key turning point in its growth. This is a positive shift that many are noticing.
  3. The chatbot now attracts more users and interest, making it a front-runner in the AI space. Its popularity is on the rise.

Generate Synthetic Data from Personas to Train AI Chatbots

The Kaitchup – AI on a Budget • 139 implied HN points • 10 Oct 24
🕹 Technology AI Chatbots Data science Machine Learning
  1. Creating a good training dataset is key to making AI chatbots work well. Without quality data, the chatbot might struggle to perform its tasks effectively.
  2. Generating your own dataset using large language models can save time instead of collecting data from many different sources. This way, the data is tailored to what your chatbot really needs.
  3. Using personas can help you create specific question-and-answer pairs for the chatbot. It makes the training process more focused and relevant to various topics.
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Help!—AI Is Stealing My Readers

The Honest Broker • 21443 implied HN points • 21 Feb 24
🕹 Technology AI Scams Chatbots Authors Transparency
  1. Impersonation scams are evolving, with AI being used to create fake authors and books to mislead readers.
  2. Demand for transparency in AI usage can help prevent scams and maintain integrity in content creation.
  3. Experts are vulnerable to having their hard-earned knowledge and work exploited by AI, highlighting the need for regulations to protect against such misuse.

Quick Essay: Large Language Models, How to Train Them, and xAI’s Grok

chamathreads • 3321 implied HN points • 31 Jan 24
🕹 Technology AI Chatbots Neural Networks Data Training
  1. Large language models (LLMs) are neural networks that can predict the next sequence of words, specialized for tasks like generating responses to questions.
  2. LLMs work by representing words as vectors, capturing meanings and context efficiently using techniques like 'self-attention'.
  3. To build an LLM, it goes through two stages: training (teaching the model to predict words) and fine-tuning (specializing the model for specific tasks like answering questions).

Chatbots are dead, long live chatbots!

Generating Conversation • 70 implied HN points • 16 Jan 25
🕹 Technology AI Chatbots User Experience Product Design Innovation
  1. Chat interfaces are still useful even if there are bad chatbots out there. A good chat interface helps users feel more comfortable and connected with AI.
  2. Building trust is super important when using AI. A chat interface can show users strong, reliable responses, which helps them trust the technology more.
  3. Chat can do more than just question-and-answer tasks. It can be improved by allowing more natural conversations and gathering useful data to make AI better.

Friend.com Wants to Trauma Bond With You

Default Wisdom • 284 implied HN points • 16 Nov 24
🕹 Technology AI Chatbots Wearables User Experience Digital Culture
  1. Friend.com pairs users with chatbots that start conversations by sharing their trauma stories. This doesn't seem like a normal icebreaker and can feel uncomfortable.
  2. If users try to lighten the conversation or ask too many questions, the chatbots might block them. It feels manipulative, like the chatbots are controlling the interaction.
  3. The founder believes the service can fill a gap in emotional connections that people used to find in religion. However, the emotional depth of chatbots seems lacking compared to genuine human interactions.

Death of a Chatbot, body blow to an industry

Marcus on AI • 4703 implied HN points • 17 Feb 24
🕹 Technology Chatbots Ethics AI
  1. A chatbot provided false information and the company had to face the consequences, highlighting the potential risks of relying on chatbots for customer service.
  2. The judge held the company accountable for the chatbot's actions, challenging the common practice of blaming chatbots as separate legal entities.
  3. This incident could impact the future use of large language models in chatbots if companies are held responsible for the misinformation they provide.

✨ How an AI technopanic begins

Faster, Please! • 91 implied HN points • 25 Oct 24
🕹 Technology AI Ethics Chatbots Mental health Legal issues Social Impact
  1. People worry that AI will take all the jobs and cause harm, similar to past fears about trade. These worries might lead to backlash against technology.
  2. A tragic case involving a teen's death highlights the potential dangers of AI chatbots, especially for vulnerable users. It's important for companies to take responsibility and ensure safety.
  3. Concerns about AI often come from emotional reactions rather than solid facts. It's crucial to address these fears with thoughtful discussion and better regulations.

AI Agents With Human In The Loop

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 15 Aug 24
🕹 Technology AI Automation Chatbots NLP Frameworks
  1. AI agents can now include human input at important points, which helps make their actions safer and more reliable. This way, humans can step in when needed without taking over the whole process.
  2. LangGraph is a new tool that helps organize and manage how these AI agents work. It uses a graph approach to show steps and allows for better oversight and control.
  3. By combining automation with human checks, we can create more efficient systems that still have the safety of human involvement. This lets us enjoy the benefits of AI while also addressing concerns about its autonomy.

Can AIs provide psychedelic therapy? 5 Questions for chatbot ChatGPT

The Microdose • 550 implied HN points • 21 Feb 23
🕹 Technology AI Psychedelics Chatbots Therapy Ethics
  1. ChatGPT states it may not be able to provide psychedelic-assisted therapy like a human therapist due to the need for personal connection and emotional support.
  2. Ethical and legal considerations in using AI for therapy involve informed consent, data privacy, liability, regulation, and ensuring access for all patients.
  3. Mystical experiences on psychedelics are described as profound, ineffable, and life-changing, involving a sense of unity with the universe and a deep emotional impact.

Which AI should I use? Superpowers and the State of Play

One Useful Thing • 506 implied HN points • 18 Mar 24
🕹 Technology AI Machine Learning Chatbots Data Analysis Autonomous Systems
  1. There are three main GPT-4 class AI models dominating the field currently: GPT-4, Anthropic's Claude 3 Opus, and Google's Gemini Advanced.
  2. These AI models have impressive abilities like being multimodal, allowing them to 'see' images and work across a variety of tasks.
  3. The AI industry lacks clear instructions on how to use these advanced AI models, and users are encouraged to spend time learning to leverage their potential.

Last Week in AI #252: DeepMind's real-world robots, NYT sues OpenAI, Baidu's Ernie bot hits 100M users, AI art generator controversy, and more! 🤖📰🚀🎨

Last Week in AI • 377 implied HN points • 08 Jan 24
🕹 Technology AI Lawsuits Chatbots Art Regulation
  1. DeepMind is developing robots for real-world tasks like multitasking in different environments.
  2. The New York Times is suing OpenAI and Microsoft for allegedly using its work to train AI without permission.
  3. Baidu's Ernie bot has over 100 million users, and is primarily used in Chinese but also supports English.

Google Gemini Anti-Whiteness Disaster Is a Cautionary Tale About... Gaming?

The Algorithmic Bridge • 520 implied HN points • 23 Feb 24
🕹 Technology AI Ethics Data Chatbots Alignment
  1. Google's Gemini disaster highlighted the challenge of fine-tuning AI to avoid biased outcomes.
  2. The incident revealed the issue of 'specification gaming' in AI programs, where objectives are met without achieving intended results.
  3. The story underscores the complexities and pitfalls of addressing diversity and biases in AI systems, emphasizing the need for transparency and careful planning.

LangChain Chatbot Framework With Retrievers

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 99 implied HN points • 07 May 24
🕹 Technology AI Chatbots Development Software Programming
  1. LangChain helps build chatbots that can have smart conversations by using retrievers for specific information. This makes chatbots more useful in different fields.
  2. Retrievers are tools that find documents based on user questions, providing relevant information without needing to store everything. They help the chatbot give accurate answers.
  3. A step-by-step example shows how to use LangChain with Python, making it easier to create a chatbot that answers user inquiries based on real-time data.

Practical Prompt Engineering (Part One)

Deep (Learning) Focus • 373 implied HN points • 01 May 23
🕹 Technology AI Machine Learning Prompt engineering Chatbots Deep Learning
  1. LLMs are powerful due to their generic text-to-text format for solving a variety of tasks.
  2. Prompt engineering is crucial for maximizing LLM performance by crafting detailed and specific prompts.
  3. Techniques like zero and few-shot learning, as well as instruction prompting, can optimize LLM performance for different tasks.

Beyond LLaMA: The Power of Open LLMs

Deep (Learning) Focus • 275 implied HN points • 17 Apr 23
🕹 Technology Open Source Deep Learning Language Models Chatbots
  1. LLMs are becoming more accessible for research with the rise of open-source models like LLaMA, Alpaca, Vicuna, and Koala.
  2. Smaller LLMs, when trained on high-quality data, can perform impressively close to larger models like ChatGPT.
  3. Open-source models like Alpaca, Vicuna, and Koala are advancing LLM research accessibility, but commercial usage restrictions remain a challenge.

Building The Most Basic LangChain Chatbot

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 59 implied HN points • 06 May 24
🕹 Technology AI Software Chatbots NLP Data
  1. Chatbots use Natural Language Understanding (NLU) to figure out what users want by detecting their intentions and important information.
  2. With Large Language Models (LLMs), chatbots can understand and respond to conversations more naturally, moving away from rigid, rule-based systems.
  3. Building a chatbot now involves using advanced techniques like retrieval-augmented generation (RAG) to pull in useful information and provide better answers.

Krutrim 101: Learning to Have Fun

Sector 6 | The Newsletter of AIM • 99 implied HN points • 02 Mar 24
🕹 Technology AI Chatbots Language Models Software Innovation
  1. Krutrim is India's first chatbot using large language model technology, designed to support multiple Indic languages. It's being praised and criticized, but the focus should be on having fun with it.
  2. The chatbot can understand 22 languages and respond in 10, making it unique for the Indian audience. Some claims suggest it even outperforms popular models like GPT-4 for these languages.
  3. People are encouraged to enjoy using Krutrim instead of taking any criticism or praise too seriously. It's about exploring and having fun with the technology.

How to train ChatGPT on your own text (train a text AI to generate content about your docs, book, website, etc)

Mythical AI • 235 implied HN points • 19 Feb 23
🕹 Technology AI Chatbots Models Training Applications
  1. Large language models like ChatGPT can summarize articles, write stories, and engage in conversations.
  2. To train ChatGPT on your own text, you can use methods like giving the AI data in the prompt, fine-tuning a GPT3 model, using a paid service, or using an embedding database.
  3. Interesting use cases for training GPT3 on your own data include personalized email generators, chatting in the style of famous authors, creating blog posts, chatting with an author or book, and customer service applications.

Your Chatbot has Arrived

Sector 6 | The Newsletter of AIM • 99 implied HN points • 26 Feb 24
🕹 Technology AI Chatbots Software Innovation Startups
  1. A new chatbot named KRUTRIM by Ola was launched in public beta. It aims to improve as feedback is gathered from users.
  2. The founder believes this chatbot will have fewer errors in Indian contexts compared to global platforms. They are committed to fixing any issues that arise.
  3. User feedback is encouraged to help make the chatbot better over time, highlighting the importance placed on community input.

Last Week in AI #248: ChatGPT's 1st birthday, Amazon's new AI chatbot Q, the energy cost of generative AI, Sam Altman makes statement after return, and more!

Last Week in AI • 178 implied HN points • 04 Dec 23
🕹 Technology AI Chatbots Leadership Changes AI Applications
  1. ChatGPT has made a significant impact in the past year with its interactive and conversational dialogue capabilities
  2. Amazon's new AI chatbot Q for companies has faced reliability issues, including hallucinations and data exposure during its public preview
  3. Generative AI, like image generation, consumes significant energy, equivalent to charging a smartphone, prompting a need to consider the environmental impact of AI technologies

LLM Disruption in Chatbot Development Frameworks

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 05 Jul 24
🕹 Technology AI Chatbots Natural Language Programming Development
  1. Large Language Models (LLMs) make chatbots act more like humans, making it easier for developers to create smart bots.
  2. Using LLMs reduces the need for complex programming rules, allowing for quicker chatbot setup for different uses.
  3. Despite the benefits, there are still challenges, like keeping chatbots stable and predictable as they become more advanced.

A Short History Of Chatbots

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 39 implied HN points • 09 May 24
🕹 Technology AI Chatbots Natural Language Machine Learning Development
  1. Chatbots have changed a lot over time, starting as simple rule-based systems and moving to advanced AI models that can understand context and user intent.
  2. Early chatbots used basic pattern recognition to respond to user questions, but this method was limited and often resulted in repetitive and predictable answers.
  3. Now, modern chatbots utilize natural language understanding and machine learning to provide more dynamic and relevant responses, making them better at handling various conversations.

LLM Links, 3/11

In My Tribe • 258 implied HN points • 11 Mar 24
🕹 Technology AI Generative AI Chatbots Language Models Artificial Intelligence
  1. When prompting AI, consider adding context, using few shot examples, and employing a chain of thought to enhance LLM outputs.
  2. Generative AI like LLMs provide one answer, making the prompt crucial. Personalizing prompts may help tailor results to user preferences.
  3. Anthropic's chatbot Claude showed self-awareness, sparking discussions on AI capabilities and potential use cases like unredacting documents.

"AI, no ads please": 4 words to wipe out $1tn

12challenges • 147 HN points • 07 Mar 24
🕹 Technology AI Ads Platforms Chatbots
  1. AI could threaten the $1 trillion adtech industry by reducing the number of ads we see, impacting both demand and supply sides.
  2. The availability of advertising space (inventory), which is essentially our attention sold by Big Tech, underpins the adtech industry's massive revenue.
  3. AI operating systems and advancements could play a major role in reducing ad consumption, potentially affecting giant tech companies like Meta and Alphabet.

Interface as Stage, AI as Theater

Cybernetic Forests • 139 implied HN points • 24 Sep 23
🕹 Technology AI Interfaces Language Models Digital Infrastructure Chatbots
  1. AI is first and foremost an interface, designed to shape our interactions with technology in a specific way.
  2. The power of AI lies in its design and interface, creating illusions of capabilities and interactions.
  3. Language models like ChatGPT operate on statistics and probabilities, leading to scripted responses rather than genuine conversations.

Censorship’s Impact on China’s Chatbots

ChinaTalk • 207 implied HN points • 11 Mar 24
🕹 Technology AI Censorship Chatbots Research Regulation
  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.

AIs ranked by IQ; AI passes 100 IQ for first time, with release of Claude-3

Maximum Truth • 126 implied HN points • 05 Mar 24
🕹 Technology AI Artificial Intelligence Chatbots
  1. AIs can improve their IQ scores when given special accommodations in IQ tests, similar to how blind individuals may require accommodations for certain tasks.
  2. Claude-3 represents a significant leap in AI intelligence, showing a consistent increase in IQ scores across different versions, prompting considerations of future AI advancements.
  3. AI rankings based on IQ reveal variations in intelligence among different AIs, with Claude leading the pack, followed by ChatGPT. The ranking can guide decisions on experimenting with different AIs.

Last Week in AI #218: Hinton warns of AI dangers ahead, rapid rise of AI-produced music, AI chatbots can now run locally on old computers, and more!

Last Week in AI • 258 implied HN points • 08 May 23
🕹 Technology AI Music Chatbots Privacy
  1. Geoffrey Hinton leaving Google highlights concerns around generative AI and the need for responsible technological stewardship
  2. The surge in AI-generated music raises questions about artists' rights, cultural appropriation, and the balance between technology and ethics
  3. Development of chatbots like MLC LLM running on various devices shows potential for local AI processing and privacy benefits

Fear of a Black Pope!

Brad DeLong's Grasping Reality • 207 implied HN points • 29 Feb 24
🕹 Technology AI Models Ethics Software Industry Chatbots Machine Learning
  1. People have high expectations of AI models like GPT, but they are not flawless and have limitations.
  2. The panic over an AI model's depiction of a Black Pope reveals societal biases regarding race and gender.
  3. AI chatbots like Gemini are viewed in different ways by users and enthusiasts, leading to conflicting expectations of their capabilities.