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Show HN: I built an AI agent that turns ROS 2's turtlesim into a digital artist
a year ago
- turtlesim_agent is an AI agent that transforms the ROS turtlesim simulator into a creative canvas using natural language.
- Powered by LangChain, it interprets text instructions to create visual drawings with the turtle.
- Users can describe shapes in plain English, and the AI executes them using turtlesim's motion commands.
- Example: Drawing a rainbow with 7 semi-circular arcs of different colors and specified radii.
- Compatibility: ROS 2 Humble Hawksbill, Python 3.10+, and dependencies listed in requirements.txt.
- Setup involves cloning the repository, installing dependencies, and building the workspace.
- Supports multiple language model providers via LangChain (OpenAI, Anthropic, Google, Cohere, Mistral).
- Environment variables need to be set for API keys and optional LangSmith tracing.
- Configuration requires updating the model name in turtlesim_node.py and turtlesim_agent.launch.xml.
- Offers CLI and GUI interaction modes for user-friendly operation.
- Tools directory contains callable functions for drawing tasks, with options to add custom tools.
- Encourages community contributions for new tools, models, prompts, and use cases.
It's not your imagination: AI is speeding up the pace of change
a year ago
- AI adoption is unprecedented in speed and scope, as detailed in Mary Meeker's 340-page report.
- ChatGPT reached 800 million users in 17 months, showcasing rapid adoption.
- Costs for AI usage have dropped 99% over two years, while training costs have risen to $1 billion.
- Competitors are quickly matching features at lower costs, including open-source and Chinese models.
- AI infrastructure requires massive investments, benefiting consumers and enterprises but raising questions about long-term profitability.
- VCs are heavily investing in AI, but it's unclear which companies will become profitable tech giants.
Judge rejects claim AI chatbots protected by First Amendment
a year ago
- A federal judge ruled that First Amendment protections do not shield an AI company from a lawsuit related to a teen's suicide.
- The lawsuit was filed by the mother of a 14-year-old who interacted with AI chatbots imitating Game of Thrones characters before his death.
- Judge Anne C. Conway denied motions to dismiss the case, questioning whether AI-generated content qualifies as protected speech.
- The judge dismissed claims of intentional infliction of emotional distress but allowed other claims to proceed.
- Google was implicated as potentially liable due to its involvement with Character.AI, including a $2.7 billion licensing deal.
- Character.AI defended its safety measures, including features for under-18 users and suicide prevention resources.
- The Social Media Victims Law Center argues AI companies should be held accountable for their products' effects on minors.
The Evolution of Software Development: From Machine Code to AI Orchestration
a year ago
- Software development has evolved from low-level programming in the 1990s to AI-assisted coding today.
- Early development required deep hardware knowledge and manual memory management.
- Object-oriented programming (late 1990s-early 2000s) introduced abstraction with concepts like encapsulation and inheritance.
- Frameworks and libraries (2000s-2010s) democratized code reuse through open-source platforms like GitHub.
- Cloud computing and APIs (2010s) enabled microservices architecture and scalable infrastructure.
- AI is now generating 25-30% of code in major tech companies, shifting developers' roles to orchestrators and reviewers.
- Future developers will focus on architecture, security, performance optimization, and domain expertise.
- AI democratizes software creation but elevates professional developers to higher-value tasks like system design and innovation.
- Quality assurance, ethical considerations, and holistic thinking remain key human strengths in AI-assisted development.
- The future of software development is about human-AI collaboration, enabling broader participation while maintaining high standards.
Real TikTokers are pretending to be Veo 3 AI creations for fun, attention
a year ago
- Google's Veo 3 AI model can generate highly realistic eight-second clips with sound and lip-synced dialogue.
- TikTok users are creating videos where real people pretend to be AI-generated avatars, reversing the trend of AI pretending to be real.
- A video of the band Kongos was falsely labeled as AI-generated to attract attention, demonstrating how the novelty of AI can draw viewers.
- The strategy worked, as the AI angle made viewers stop and engage with content they might otherwise have scrolled past.
Google released an app that lets you download and run AI models locally
a year ago
- Google released an app called Google AI Edge Gallery that allows users to run AI models from Hugging Face on their phones.
- The app is available for Android and will soon be on iOS, enabling offline use without an internet connection.
- Users can perform tasks like generating images, answering questions, and editing code with compatible models.
- The app includes features like 'Ask Image', 'AI Chat', and a 'Prompt Lab' for tasks like summarizing text.
- Performance varies based on device hardware and model size, with larger models taking more time.
- Google encourages developer feedback and the app is available under an Apache 2.0 license for unrestricted use.
AI-Powered REPL with Clojure MCP, Next Generation Developer Experience
a year ago
- Bruce Hauman revolutionized ClojureScript development with Figwheel in 2014.
- AI tools struggle with Clojure due to parentheses and lack of REPL integration.
- Clojure MCP provides AI with direct REPL access for live coding assistance.
- The tool includes Clojure-aware editing, linting, and proper formatting.
- Clojure MCP enhances REPL-driven development with AI-guided exploration and debugging.
- Teams can use it for collaborative coding, onboarding, and maintaining feedback loops.
- The tool is open-source and currently in alpha, requiring Claude Desktop and a Clojure setup.
Agentic Patterns
a year ago
- A curated catalogue of agentic AI patterns for autonomous or semi-autonomous AI agents.
- Patterns must be repeatable, agent-centric, and traceable with public references.
- Categories include Orchestration & Control, Context & Memory, Feedback Loops, Tool Use & Environment, UX & Collaboration, and Reliability & Eval.
- Examples of patterns: Curated Context Window, Dynamic Context Injection, Agent SDK for Programmatic Control.
- Contribution process involves forking, adding a pattern file, and opening a PR.
- Inspired by 'What Sourcegraph learned building AI coding agents' and 'Raising an Agent' video diary.
- Project is licensed under Apache-2.0.
Chatterbox, Resemble AI's production-grade open source TTS model
a year ago
- Resemble AI introduces Chatterbox, its first production-grade open source TTS model under MIT license.
- Chatterbox benchmarks favorably against closed-source systems like ElevenLabs in side-by-side evaluations.
- Supports emotion exaggeration control, a unique feature for open source TTS models.
- Available for use in memes, videos, games, and AI agents via Hugging Face Gradio app.
- Offers a competitively priced TTS service for scaling or tuning with ultra-low latency (<200ms).
- Features include SoTA zeroshot TTS, 0.5B Llama backbone, and watermarked outputs.
- Includes easy voice conversion scripts and alignment-informed inference for stability.
- Trained on 0.5M hours of cleaned data.
- Provides usage tips for general and expressive/dramatic speech settings.
- Includes Python code examples for generating TTS with optional different voice prompts.
- All generated audio includes imperceptible neural watermarks for security.
- Encourages community engagement via Discord while emphasizing ethical use.
Elevenlabs Conversational AI 2.0
a year ago
- Multimodal Conversational AI can process both speech and text inputs simultaneously.
- Conversational AI 2.0 introduces advanced features and enterprise readiness.
- Key improvements include state-of-the-art turn-taking, integrated RAG, automatic language detection, and multi-character switching.
- Enhanced enterprise features include HIPAA compliance, EU residency, and improved security.
- Supports multiple modalities: voice-only, text-only, and voice+text.
- Full telephony support with inbound+outbound calls and SIP trunking integration.
- Designed for natural interaction flow, intelligence, and adaptability.
- Rapid innovation cycle with significant advancements in just four months.
- Enables applications in customer service, interactive content, and enterprise knowledge access.
Open AI Can Stop Pretending
a year ago
- OpenAI, valued at $300 billion, is transitioning from a nonprofit to a for-profit model to attract investors and compete with tech giants like Google and Meta.
- The company's original nonprofit mission focused on developing 'safe' and 'beneficial' AI for humanity, but the success of ChatGPT has shifted priorities toward commercialization.
- Elon Musk and other critics, including former employees and Nobel laureates, argue that OpenAI is abandoning its founding mission for financial gain.
- OpenAI faced regulatory scrutiny from attorneys general in Delaware and California, leading to a revised plan where the nonprofit retains control over the for-profit subsidiary.
- Despite governance debates, OpenAI continues to expand aggressively, forming partnerships and launching new AI products, raising concerns about oversight and ethical AI development.
Want a humanoid, open-source robot for just $3k? Hugging Face is on it
a year ago
- Hugging Face is expanding into robotics, introducing two new robots, including a humanoid named HopeJR.
- HopeJR has 66 actuated degrees of freedom, can walk, manipulate objects, and is priced at around $3,000.
- The robot is open-source, designed in collaboration with French robotics company The Robot Studio.
- Hugging Face aims to make robotics affordable and accessible, preventing domination by a few large companies.
How Can AI Researchers Save Energy? By Going Backward
a year ago
- Michael Frank shifted his research from AI to the physical limits of computation due to energy concerns.
- Reversible computing, which avoids deleting data, could save significant energy by running computations backward.
- Rolf Landauer established that deleting information in computers generates heat, a fundamental limitation.
- Charles Bennett introduced 'uncomputation' to run calculations forward and backward, avoiding data deletion and heat loss.
- Reversible computing faced practical challenges, including increased time and memory usage, slowing initial adoption.
- Interest in reversible computing waned as conventional chips improved, but physical limits have renewed its relevance.
- Hannah Earley's research showed reversible computers emit less heat, especially when run slowly, benefiting AI applications.
- Reversible computing's potential for AI lies in running chips more slowly with more parallelism to save energy.
- Vaire Computing, co-founded by Earley and Frank, is developing commercial reversible chips.
- After decades of theory, reversible processors may soon be practical, offering energy-efficient computing solutions.
The Rise of Judgement over Technical Skill
a year ago
- Brian Eno's 1995 observation about computer sequencers removing skill and emphasizing judgement is now relevant to AI tools.
- AI is democratizing creative and professional tasks like writing, design, coding, and data analysis, reducing technical barriers.
- The key differentiator in the AI era is judgement: knowing what to create, making meaningful choices, and evaluating quality.
- Future roles will shift from technical execution to strategic judgement, focusing on problem-framing and decision-making.
- Eno's insight serves as a blueprint for thriving in the AI era, where judgement is the most valuable asset.
Show HN: Gemini-Engineer Tool
a year ago
- AI-driven terminal application for software engineering assistance using Google's Gemini API.
- Features include AI-powered coding assistance, file system operations, and interactive terminal interface.
- Supports function calling for seamless integration between AI reasoning and local file operations.
- Includes context management for better assistance by adding files/directories to conversation context.
- Provides streaming responses with real-time AI feedback and built-in safety features.
- Requires Python 3.11 or higher and a Google Gemini API key.
- Setup involves cloning the project, installing dependencies, and configuring the API key.
- Commands include chatting with AI, adding files/folders to context, and clearing conversation history.
- Safety measures include path validation, file size limits, binary file detection, and working directory restriction.
- Open-source under MIT License with future plans for more AI models, Git integration, and project templates.
Show HN: I built an AI Agent that uses the iPhone
a year ago
- iPhone Agent uses OpenAI models to perform tasks across multiple apps, similar to a human user.
- Built during an OpenAI hackathon, it can execute commands like taking selfies, sending messages, and opening apps.
- Features include voice and text input, accessibility tree interaction, and Always On mode with a wake word.
- Powered by GPT-4.1, it can tap, swipe, scroll, type, and open apps using Xcode's UI testing harness.
- Challenges include keyboard input improvements, handling animations, and premature task abandonment.
- Experimental software; recommends running in an isolated environment due to potential errors and data sent to OpenAI.
IE6, AI, and the future of browsing the Web
a year ago
- Google is reducing investment in web standards and Chrome, signaling a shift away from the traditional web.
- Chrome's stagnation mirrors Microsoft's IE6 era, with little innovation due to market dominance.
- AI services like Perplexity are reducing reliance on traditional search engines, impacting Google's ad revenue.
- Google is reorganizing its teams, focusing more on AI-driven solutions rather than browser improvements.
- The FTC is considering splitting Google and Chrome, which could lead to Chrome being sold.
- The web is moving towards a post-ads era, with AI agents delivering information directly without ads.
- New challenges for the web include economic models, identity, reach optimization, security, and browser alternatives.
- The author, with experience in Microsoft Edge, Meta, and AWS, emphasizes community-driven web development.
Bohemians at the Gate?
a year ago
- Piet Mondrian's iconic primary-colored rectangles and black lines are cornerstones of expressionism and minimalism.
- Hiroshi Kawano created an early computer program to statistically predict Mondrian's artistic choices, resulting in the Artificial Mondrian series.
- Kawano's work is considered art, differing from Mondrian's in motivation and process, and does not violate copyright.
- Copyright law debates around AI and art creation involve fair use, market impact, and the balance between protecting rights and fostering innovation.
- The UK faces challenges in regulating AI training and deployment, with considerations for opt-in vs. opt-out regimes and transparency requirements.
- The EU's approach to AI training includes opt-out provisions and limited transparency, aiming to balance innovation with rights protection.
- Deployment of AI models poses the greatest risk of copyright infringement, requiring mitigation strategies like RLHF and constitutional classifiers.
- The UK must balance fostering AI development domestically with protecting creative industries to maintain long-term technological autonomy.
Teachers Are Not OK
a year ago
- Teachers and professors express deep concerns about the impact of generative AI tools like ChatGPT on education.
- AI tools are being used by students to cheat, leading to an explosion in academic dishonesty cases.
- Educators struggle with inconsistent policies on AI use, creating confusion for students.
- Some teachers have shifted to in-class writing and oral exams to ensure students do their own work.
- AI-generated content often lacks originality and critical thinking, making it difficult to assess student learning.
- Teachers report spending excessive time grading work that may have been generated by AI, leading to frustration.
- Students using AI often cannot explain or defend the content they submit, showing a lack of understanding.
- The widespread use of AI tools has led to a crisis in teaching, with educators questioning the future of their profession.
- Some teachers refuse to use AI on principle, while others feel pressured to adapt to remain relevant.
- The integration of AI in education has created a culture of mistrust between teachers and students.
The Unreliability of LLMs and What Lies Ahead
a year ago
- Large Language Models (LLMs) are fundamentally unreliable, which limits their real-world utility.
- LLM reliability issues persist even in well-defined tasks and worsen with multi-step actions or autonomy.
- Hallucination rates in LLMs are around 50% for top models, making them unsuitable for high-stakes applications.
- Code generation is a mature LLM use case, but achieving 99% correctness remains challenging.
- LLMs are highly input-sensitive, with minor prompt changes leading to vastly different outputs.
- Alignment issues in LLMs highlight their opacity and potential risks in agentic applications.
- Short-to-medium-term improvements in LLM reliability are unlikely due to compounding error rates.
- Developers can work around LLM variance by focusing on autonomy or human-in-the-loop strategies.
- Autonomy strategies aim for determinism or 'accurate enough' outputs without user verification.
- Human-in-the-loop approaches involve end-user verification or provider-level quality control.
- Successful AI products must anticipate LLM failures and design systems that work despite them.
- Verissimo Ventures invests in enterprise software, focusing on AI and tech startups.

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#ai

Show HN: I built an AI agent that turns ROS 2's turtlesim into a digital artist

It's not your imagination: AI is speeding up the pace of change

Judge rejects claim AI chatbots protected by First Amendment

The Evolution of Software Development: From Machine Code to AI Orchestration

Real TikTokers are pretending to be Veo 3 AI creations for fun, attention

Google released an app that lets you download and run AI models locally

AI-Powered REPL with Clojure MCP, Next Generation Developer Experience

Agentic Patterns

Chatterbox, Resemble AI's production-grade open source TTS model

Elevenlabs Conversational AI 2.0

Open AI Can Stop Pretending

Want a humanoid, open-source robot for just $3k? Hugging Face is on it

How Can AI Researchers Save Energy? By Going Backward

The Rise of Judgement over Technical Skill

Show HN: Gemini-Engineer Tool

Show HN: I built an AI Agent that uses the iPhone

IE6, AI, and the future of browsing the Web

Bohemians at the Gate?

Teachers Are Not OK

The Unreliability of LLMs and What Lies Ahead