The hottest Chatbots Substack posts right now

And their main takeaways
Category
Top Technology Topics

Hallucinations Acche Hain

Sector 6 | The Newsletter of AIM • 19 implied HN points • 18 Sep 23
🕹 Technology AI Chatbots Creativity Innovation Digital Tools
  1. Hallucinations in AI models can be a double-edged sword; they can lead to creativity but also cause issues with trust. It's important to think about how much we can rely on these chatbots.
  2. Some researchers believe that hallucinations help chatbots become better partners in creativity. They argue that these 'mistakes' can lead to unexpected and innovative ideas.
  3. Despite the risks, there's a fascination with the unpredictable nature of AI chatbots. Embracing their quirks could potentially unlock new ways of thinking and collaborating.

Error 404: Google Search Not Found

Sector 6 | The Newsletter of AIM • 19 implied HN points • 26 Jun 23
🕹 Technology AI Search Chatbots Analytics Innovation
  1. Search engines are changing a lot, and soon we might just chat with AI instead of typing our questions. They might still show some links, but the focus will be on conversation.
  2. Google had the goal of using AI in their search from the very beginning. Even in 2002, they tried a service where humans would answer questions, but they quickly realized they needed AI to handle all the inquiries.
  3. Larry Page, one of Google's founders, said that they would know their mission was complete once their search engine was fully powered by AI. They see the future of search as relying on artificial intelligence.
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Baidu's Ernie Bot: Trying to Ern the Chatbot Crown *

Tech Buzz China Insider • 19 implied HN points • 14 Apr 23
🕹 Technology Artificial Intelligence Chatbots Machine Learning Cloud Computing Tech industry
  1. Ernie Bot by Baidu competes in the AI chatbot market, facing challenges but promising multi-modal capabilities and potential in China's AI landscape.
  2. Baidu leads in LLMs in China but lags behind OpenAI in model power, aiming to monetize Ernie Bot through enterprise solutions and expecting a revenue of up to 1 billion RMB in 2023.
  3. Large AI model training costs offer tech giants an advantage, while Baidu navigates export controls & domestic AI GPU options to meet China's AI needs.

The value-destroying potential of AI

Apperceptive (moved to buttondown) • 32 implied HN points • 31 Jul 23
🕹 Technology AI Software Metrics Chatbots Applications
  1. Many businesses struggle to measure the true value of implementing AI solutions.
  2. The key problem lies in defining and measuring what 'good driving' or 'good writing' actually means.
  3. Executives should be cautious about overly relying on AI like ChatGPT for creative tasks, as they may miss out on the unique perspectives and insights that humans offer.

A Not-So-Quick Overview of the Chinese AI Scene

State Space Adventures • 2 HN points • 30 May 24
🕹 Technology Chatbots LLMs Competitive Landscape
  1. The Chinese AI scene is highly competitive, with companies developing advanced models at a rapid pace to outdo each other.
  2. Chinese AI companies are engaging in a pricing war to make their models more accessible, leading to reduced costs and free versions of top models.
  3. Chinese tech giants like Baidu, Tencent, Alibaba, and ByteDance are investing in AI development and competing against each other in the chatbot space.

Week 78 - E7 - 🚀🤖✨Transform Your Business with Next-Gen RAG Digital Assistants

The Product Channel By Sid Saladi • 13 implied HN points • 18 Feb 24
🕹 Technology AI Machine Learning Product Management Chatbots Enterprise Solutions
  1. Large Language Models (LLMs) trained on Private Data are becoming popular for creating AI assistants that can engage customers, answer questions, assist employees, and automate tasks.
  2. The Retrieval-Augmented Generation (RAG) framework enhances the capabilities of LLMs by incorporating external, real-time information into AI responses, revolutionizing the accuracy and relevance of generated content.
  3. Implementing RAG in enterprises through steps like choosing a foundational LLM, preparing a knowledge base, encoding text into embeddings, implementing semantic search, composing final prompts, and generating responses can transform business operations by empowering employees, enhancing customer engagement, streamlining decision-making, driving innovation, and optimizing content strategy.

ChatGPT Models, Structure & Input Formats

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 11 Apr 23
🕹 Technology AI Chatbots APIs Data NLP
  1. ChatGPT is more than just a large language model; it's a conversational service that uses AI to manage conversations and gather data from different sources.
  2. Plugins allow ChatGPT to connect with other applications, making it more versatile and capable of performing various tasks, similar to apps in an app store.
  3. Using the ChatGPT API requires understanding specific formats for input and output, which helps in building custom applications with the AI.

Prompt Chaining

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 06 Apr 23
🕹 Technology AI Programming Chatbots User Interface Data Transformation
  1. Visual Programming tools are being used to connect prompts in applications, making it easier to create conversational interfaces.
  2. Chaining prompts involves transforming and organizing data from responses to ensure better output and decision-making in AI applications.
  3. Good design of these tools includes making it easy to build, edit, and debug chains while also allowing users to interact flexibly with the AI.

OpenAI Live Update on May 13: ChatGPT and GPT-4 Surprises?

AI Disruption • 2 HN points • 10 May 24
🕹 Technology AI Updates Chatbots OpenAI
  1. OpenAI will livestream an update on May 13 regarding ChatGPT and GPT-4 improvements.
  2. There is speculation about a potential GPT-4.5 variant with enhanced features like better understanding, more current knowledge, and improved performance.
  3. The rumored GPT-4.5 improvements suggest advancements in design, functionality, language handling, and response quality.

These Are The Challenges When Creating A LLM Based Conversational Interface

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 19 implied HN points • 01 Mar 23
🕹 Technology AI LLMs Chatbots NLP Applications
  1. Creating conversational interfaces with language learning models (LLMs) is tricky because the responses can be very different each time. This makes it hard to keep conversations flowing smoothly.
  2. If you change something small in the middle of a conversation, it can mess up everything that comes after. This makes planning the conversation a bit complicated.
  3. As these chatbots get more complex, we can use groups of connected steps to manage the conversation better. Future tools might make it easier for people to design these conversations without coding.

Sampler

Internal exile • 26 implied HN points • 26 May 23
🕹 Technology AI Social media Writing Chatbots Ethics
  1. AI can be manipulated through poisoning attacks, affecting outcomes and creating incentives for spammers and tech companies.
  2. Influencers drive the trend of 'kinetic' food in restaurants, emphasizing visual appeal for videos over taste.
  3. The 'sharing economy' has shifted from genuine sharing to profit-driven exploitation, impacting workers and service users.

GPTs: What are they good for?

Causal Deference • 8 implied HN points • 17 Nov 23
🕹 Technology AI Chatbots Search Machine Learning Innovation
  1. GPTs can be used to create custom chatbots, but the killer app is still elusive.
  2. OpenAI's GPTs feature allows for powerful functionality by combining saved prompts with backend tools like Bing search.
  3. There is potential in developing GPT-based systems with better posting assistance, context awareness, and batch processing for more compelling applications.

AI and the Third Age of Human-Computer Interaction

Year 2049 • 15 implied HN points • 14 Apr 23
🕹 Technology AI Interfaces UX Design Chatbots Machine Learning
  1. In the First Age of Human-Computer Interaction, communication with machines was through code like punched cards.
  2. The Second Age introduced point-and-click interfaces, making interactions more visual and user-friendly.
  3. The Third Age brings natural language interactions where AI understands us, like with ChatGPT, changing how we interact with technology.

Future Bites #2

Year 2049 • 13 implied HN points • 03 Mar 23
🕹 Technology AI Regulation Health tech Space Tech Chatbots Wearable Tech
  1. Apple is working on noninvasive blood glucose tracking tech for the Apple Watch to help monitor health and prevent diseases.
  2. The EU is looking to regulate AI through the proposed AI Act, including risk levels, transparency requirements, and focus on high-risk applications.
  3. Blue Origin is developing solar cells using simulated lunar soil to support sustainable human presence on the Moon, collaborating with NASA.

Why AI can't replace customer service 📞

Year 2049 • 8 implied HN points • 11 Aug 23
🕹 Technology AI Customer Service Chatbots Productivity
  1. AI can't fully replace human customer service agents due to limitations and the importance of human connection.
  2. AI chatbots are improving but people still prefer interacting with human agents for emotional support and flexibility.
  3. The potential lies in having AI and human agents work together to enhance productivity and performance in customer service.

The Diminishing Charm of AI: Are Chatbots Losing Their Luster?

The AI Observer • 3 implied HN points • 20 Feb 24
🕹 Technology AI Machine Learning Chatbots
  1. AI models are experiencing performance degradation over time due to user interactions, highlighting the need for ongoing monitoring and adaptation to maintain effectiveness.
  2. Chatbots have shifted from unpredictable entities to function-focused tools, raising concerns about their lack of engagement and personality.
  3. Model drift, including concept drift and data drift, can lead to unreliable machine learning predictions, impacting decision-making, customer satisfaction, financial outcomes, and trust in AI systems.

Beyond ChatGPT: Exploring New Frontiers for NLP Specialists in a World of Advanced AI Chatbots

AI Progress Newsletter • 3 implied HN points • 22 Apr 23
🕹 Technology NLP Chatbots Fact-checking AI Research
  1. Developing domain-specific chatbots tailored to industries like healthcare, finance, and legal services can provide specialized support and knowledge to users.
  2. Automated fact-checking systems using NLP techniques aim to verify the accuracy of information to combat misinformation in news articles and social media.
  3. NLP specialists have various opportunities to explore beyond ChatGPT, as the field is evolving with new challenges and possibilities.

The Third Gemini

Don't Worry About the Vase • 1 HN point • 15 Feb 24
🕹 Technology AI Artificial Intelligence Comparisons Chatbots Features
  1. Gemini Advanced shows potential in some areas but is perceived as slightly behind ChatGPT overall.
  2. Gemini Advanced is faster and offers unlimited messages compared to ChatGPT, making it beneficial for workflow.
  3. Gemini Advanced has pros like good explanations, faster response, and Google integration, but also cons like being less flexible and refusing to answer more frequently.

Trying all the alternatives to ChatGPT

Boris Again • 1 HN point • 22 Apr 23
🕹 Technology AI Models Alternatives Chatbots Artificial Intelligence Programming
  1. Alternative AI models like Claude, Dolly V2, and Alpaca offer different features and prices compared to ChatGPT and GPT-4.
  2. Each model has its unique strengths and weaknesses, like speed, coherence, licensing restrictions, and price per token.
  3. While some models are self-hosted and free to access, others may require a request or have specific pricing structures.

PROJECT PARAKEET

Unbound • 1 HN point • 18 Mar 23
🕹 Technology AI Chatbots Creativity Ethics
  1. The writing by AI may lack originality and expressiveness, despite being able to mimic human language well.
  2. Critics highlight the controlled nature of AI chatbot conversations as a realistic feature that some find attractive in a sensitive societal context.
  3. There are concerns that AI's continuous learning from existing texts might lead to a decline in originality and quality of human writings, potentially resulting in a chaotic situation.

Chat Limitations, Rise of LLM’s, Generative UIs

Microfrontends, Architecture and Trade-offs • 0 implied HN points • 14 Apr 23
🕹 Technology AI UI Design Software Development Chatbots
  1. Consider the nature of the task to determine the most effective interaction mode, as chat may not always be optimal.
  2. The improvement of Large Language Models (LLMs) could lead to a world where UIs are generated on demand based on user intent.
  3. Generative UIs could self-assemble based on user requests and adapt to tasks, offering a dynamic and efficient user experience.