From 45 items, 36 important content pieces were selected
- Alibaba Unveils Qwen3.8-Max AI Model ⭐️ 9.0/10
- LLMs Reward Expertise in Software Development ⭐️ 8.0/10
- Advances in Math and Theoretical Computer Science ⭐️ 8.0/10
- Devtools Must Be Open Source ⭐️ 8.0/10
- Cloudflare Optimizes AI Models ⭐️ 8.0/10
- ComfyUI Supports MiniMax H3 with Open Weights ⭐️ 8.0/10
- Retyping LLM-Generated Code Prevents Cognitive Debt ⭐️ 8.0/10
- Andy Pavlo Joins ClickHouse ⭐️ 8.0/10
- IBM: 92% of AI Breach Victims Lacked Access Controls ⭐️ 8.0/10
- AI Drives 55% of Cybercrimes in Africa ⭐️ 8.0/10
- Two teams solved the same quantum crypto problem using GPT-5.6 just three hours apart ⭐️ 8.0/10
- After killer quarter, Palantir CEO Alex Karp calls AI industry ‘Marxist’ ⭐️ 8.0/10
- Design Arena creators raise $7.9 million to bring taste to AI models ⭐️ 8.0/10
- Congress’ favorite AI tool? ChatGPT ⭐️ 8.0/10
- A Marc Benioff-backed startup thinks AI can solve the AI deployment problem ⭐️ 8.0/10
- EPA says power for data centers can sidestep pollution laws ⭐️ 8.0/10
- MIT, Harvard, Stanford & Caltech write their own ML course notes instead of using a textbook — I catalogued the best ones ⭐️ 8.0/10
- Open always wins: How China is using the open source playbook to dominate AI’s next chapter ⭐️ 8.0/10
- MIT Tech Review on AI agents “lying” is really about Goodhart’s law ⭐️ 8.0/10
- AI automation is eating the parts of indie building I actually enjoyed, anyone else feeling this? ⭐️ 8.0/10
- What Are Companies Getting for All That A.I. Spending? A new field of “tokenomics” has emerged to measure the return on all the money companies are pouring into artificial intelligence. (Gift Article) ⭐️ 8.0/10
- Twenty Years of Pandoc ⭐️ 7.0/10
- Don’t be a meat proxy ⭐️ 7.0/10
- Quoting David Crawshaw’s prompt ⭐️ 7.0/10
- Unicorn, pelican, Middle-earth: OpenAI co-founder Karpathy is looking for the next AI vibe test ⭐️ 7.0/10
- AWS is helping vibe-coding startup Superblocks, and the implications are big ⭐️ 7.0/10
- Influencers draw backlash for attending OpenAI’s first luxury trip ⭐️ 7.0/10
- Apple finally fixed Siri. So why does it feel anticlimactic? ⭐️ 7.0/10
- Thoughts on use of AI slop in politics? ⭐️ 7.0/10
- What your ideal AI work interface would look like ⭐️ 7.0/10
- Built my first AI agent in Java (no Python) using LangChain4j — took about 30 minutes ⭐️ 7.0/10
- Spotify AI (Kit) wants to compete with Cowork? ⭐️ 7.0/10
- I’m building an AI tool for rehabilitation. Here’s one problem I keep running into. ⭐️ 7.0/10
- AI / Machine Learning Is Booming, So Why Isn’t Anyone Hiring? ⭐️ 7.0/10
- Quoting Steve Yegge ⭐️ 6.0/10
- Do you regularly chat with AI? Share your experience in a psychology study ⭐️ 6.0/10
Alibaba Unveils Qwen3.8-Max AI Model ⭐️ 9.0/10
Alibaba has introduced its new flagship AI model, Qwen3.8-Max, which is capable of handling complex tasks autonomously over extended periods with 2.4 trillion parameters. The model is designed to perform tasks such as reproducing research papers and designing chips on its own over days at a time. The introduction of Qwen3.8-Max is significant as it represents a major breakthrough in handling complex, long-horizon tasks, which could have substantial implications for various industries. This development could lead to increased efficiency and productivity in fields such as research and design. Qwen3.8-Max is an open-weight AI model, which means its learned parameters are publicly available, allowing others to download and use the model. The model’s 2.4 trillion parameters make it one of the largest and most powerful AI models available.
rss · The Decoder · Aug 3, 10:48
Background: Large language models like Qwen3.8-Max are a type of artificial intelligence designed to process and understand human language. These models are trained on vast amounts of text data and can be used for a variety of tasks such as language translation, text generation, and question answering. Long-horizon tasks refer to complex tasks that require the model to plan and execute over extended periods, often involving multiple steps and complex decision-making.
References
Tags: #AI products, #AI research, #Machine Learning
LLMs Reward Expertise in Software Development ⭐️ 8.0/10
A recent article discusses how Large Language Models (LLMs) reward expertise in software development, highlighting the importance of familiarity with codebases and the limitations of relying solely on AI. Community comments provide valuable insights on the effectiveness of LLMs in software development. This is significant because it highlights the importance of human expertise in software development, even with the increasing use of AI-powered tools. The effectiveness of LLMs in software development has implications for the future of the industry and the role of human developers. Notable technical details include the importance of familiarity with codebases and the limitations of relying solely on AI, as well as the potential for LLMs to amplify human expertise. The article highlights the need for a balanced approach that combines human expertise with AI-powered tools.
hackernews · MaxMussio · Aug 3, 21:13 · Discussion
Background: Large Language Models (LLMs) are a type of AI model trained on vast amounts of text data, enabling them to generate, summarize, and analyze text in various contexts. Codebases refer to collections of source code used to build software components, and familiarity with codebases is essential for effective software development. The use of LLMs in software development is a growing trend, with potential benefits including improved productivity and reduced errors.
Discussion: Community comments highlight the importance of human expertise in software development, with some commenters noting that LLMs can amplify human expertise but should not replace it. Others emphasize the need for a balanced approach that combines human expertise with AI-powered tools.
Tags: #AI products, #Software engineering, #LLMs, #Expertise in AI
Advances in Math and Theoretical Computer Science ⭐️ 8.0/10
The article highlights ten significant advances in mathematics and theoretical computer science, with a focus on the impact of AI on these fields. Large language models (LLMs) have been shown to generate and validate math proofs, leading to exponential progress in these areas. These advances are significant because they demonstrate the potential for AI to accelerate progress in mathematics and theoretical computer science, leading to breakthroughs in fields such as cryptography and algorithm design. The impact of LLMs on these fields could be profound, enabling new discoveries and innovations. The use of LLMs in mathematics and theoretical computer science has enabled the generation and validation of math proofs, allowing for exponential progress in these areas. However, it is noted that not all math problems can be solved by LLMs, and human intuition and creativity are still essential for making new discoveries.
hackernews · milkshakes · Aug 3, 16:27 · Discussion
Background: Theoretical computer science is a subfield of computer science and mathematics that focuses on the abstract and mathematical foundations of computation. It encompasses a wide range of topics, including algorithms, data structures, computational complexity, and cryptography. The use of LLMs in this field is a recent development, with potential applications in areas such as automated proof verification and mathematical discovery.
Discussion: The community discussion highlights the potential for LLMs to revolutionize mathematics and theoretical computer science, with some commentators noting that the ability of LLMs to generate and validate math proofs could lead to exponential progress in these areas. However, others caution that human intuition and creativity are still essential for making new discoveries.
Tags: #AI Research, #Mathematics, #Theoretical Computer Science, #LLMs, #AI Applications
Devtools Must Be Open Source ⭐️ 8.0/10
The author argues that devtools must be open source, citing the benefits of transparency and customizability, and sparking a debate on the role of large language models in software development and maintenance. This debate has garnered insightful comments from the community, including diverse viewpoints on the role of LLMs in modifying software. This discussion matters because it highlights the importance of open-source devtools in ensuring transparency, customizability, and community involvement in software development. The integration of LLMs in software development also raises questions about the future of coding and the role of human developers. Notable technical details include the potential inefficiencies of relying on nightly cron jobs to update software and the limitations of using LLMs to modify code. The community comments also highlight the importance of considering the practicalities of maintaining and updating devtools.
hackernews · bryanmikaelian · Aug 3, 14:15 · Discussion
Background: The concept of open-source devtools is not new, but the integration of LLMs in software development has added a new layer of complexity to the discussion. Open-source devtools have long been recognized for their benefits, including increased transparency, customizability, and community involvement. However, the use of LLMs raises questions about the role of human developers and the potential risks of relying on automated coding tools.
References
Discussion: The community discussion is diverse, with some commenters agreeing that devtools should be open source, while others express concerns about the practicalities of maintaining and updating devtools. Some commenters also highlight the potential inefficiencies of relying on LLMs to modify code and the importance of considering the role of human developers in the process.
Tags: #open source, #devtools, #LLMs, #software engineering
Cloudflare Optimizes AI Models ⭐️ 8.0/10
Cloudflare has shared its approach to running smaller, faster, and safer AI models like Kimi and GLM at scale, utilizing techniques such as quantization to improve performance. This approach enables the company to optimize AI models for better efficiency and security. This development is significant as it showcases Cloudflare’s efforts to balance the performance and security of AI models, which is crucial for the broader adoption of AI technologies. The optimization of AI models can lead to improved efficiency, reduced costs, and enhanced user experience. The optimization technique used by Cloudflare involves quantization, which reduces the precision of model weights and activations to reduce computational requirements. This approach allows for faster inference times and lower memory usage, making it suitable for large-scale deployments.
hackernews · ascorbic · Aug 3, 17:08 · Discussion
Background: Cloudflare is a cloud-based platform that provides a range of services, including content delivery, security, and performance optimization. The company has been investing in AI research and development to improve its services and provide better user experiences. Kimi and GLM are AI models developed by other companies, and Cloudflare is working to optimize these models for its own use cases.
Discussion: The community discussion around this topic is focused on the technical details of quantization and its impact on model performance. Some commenters have raised concerns about the potential degradation of model quality due to quantization, while others have suggested alternative approaches to optimization. Additionally, some users have expressed interest in learning more about the job opportunities related to AI model optimization at Cloudflare.
Tags: #AI Optimization, #Cloudflare, #Quantization, #AI Models, #Computer Vision
ComfyUI Supports MiniMax H3 with Open Weights ⭐️ 8.0/10
ComfyUI announces day-0 support for MiniMax H3, featuring open weights, native audio, and 2K video capabilities, with a 66% reduction in memory footprint. This development enables significant model optimization and impressive video generation capabilities. This development is significant as it showcases the potential for AI model optimization, enabling more efficient use of resources and improved performance. The integration of MiniMax H3 with ComfyUI also highlights the growing importance of multimodal AI models in various applications. The MiniMax H3 model features a 66% reduction in memory footprint, from 123.6 GB to 42.5 GB, and supports native audio and 2K video generation. ComfyUI’s day-0 support enables seamless integration with the model, allowing users to leverage its capabilities.
hackernews · vblanco · Aug 3, 13:34 · Discussion
Background: ComfyUI is an open-source, node-based program that allows users to generate images and videos from text prompts, using diffusion models such as Stable Diffusion. MiniMax H3 is a multimodal AI model developed by MiniMax Group, a Chinese AI company. The model is designed to support unified understanding of multimodal contexts composed of text, images, video, and audio.
References
Discussion: Community members discussed the potential applications of the MiniMax H3 model, including its use in traditional rendering and potential limitations. Some users shared their experiences with the model, noting its impressive performance and areas for improvement.
Tags: #AI products, #Computer vision, #AI/ML research, #Software engineering, #Video generation
Retyping LLM-Generated Code Prevents Cognitive Debt ⭐️ 8.0/10
The article discusses the benefits of manually retyping code generated by Large Language Models (LLMs) to prevent cognitive debt and improve understanding. This approach allows developers to better comprehend the code and reduce reliance on AI-generated solutions. This approach is significant because it highlights the importance of human understanding and involvement in software development, even with the increasing use of AI-generated code. By retyping LLM-generated code, developers can ensure they truly comprehend the code and reduce the risk of cognitive debt. The article suggests that manually retyping LLM-generated code can help developers identify potential issues and improve their overall understanding of the code. However, some community members argue that this approach may not be efficient and could be seen as a step backward in software development.
hackernews · mpweiher · Aug 3, 09:32 · Discussion
Background: Large Language Models (LLMs) are AI models trained on vast amounts of text data for natural language processing tasks. They can generate, summarize, translate, and analyze text, but may produce biased or inaccurate results if trained on flawed data. Cognitive debt refers to the concept that relying too heavily on AI-generated solutions can lead to a lack of understanding and comprehension of the underlying code or concepts.
References
Discussion: The community discussion is divided, with some members agreeing that manually retyping LLM-generated code is beneficial for understanding and others arguing that it is inefficient and unnecessary. Some members also share their personal experiences and alternative approaches to working with LLM-generated code.
Tags: #AI products, #software engineering, #LLM, #cognitive debt
Andy Pavlo Joins ClickHouse ⭐️ 8.0/10
Andy Pavlo has joined ClickHouse to establish ClickHouse Labs, a significant move for the database research community. This new development is expected to drive innovation in the field of online analytical processing (OLAP). The establishment of ClickHouse Labs matters because it brings together a renowned expert in database research with a leading OLAP database management system, potentially leading to breakthroughs in data analysis and processing. This collaboration can impact the broader ecosystem of business intelligence and data-driven decision-making. ClickHouse Labs will focus on advancing the state-of-the-art in OLAP and related technologies, with Andy Pavlo at the helm. The lab’s work will build upon ClickHouse’s column-oriented database management system, which is optimized for real-time analytical reporting.
hackernews · nikolay_sivko · Aug 3, 14:09 · Discussion
Background: Online Analytical Processing (OLAP) is a technology that enables fast and efficient analysis of data from multiple dimensions. ClickHouse is an open-source, column-oriented database management system designed for OLAP, allowing for real-time generation of analytical reports using SQL queries. The company has received significant funding and is valued at over $6 billion.
References
Discussion: The community is excited about the potential of ClickHouse Labs, with some members discussing the convergence of OLAP products and the future of database research. Others have expressed hope that ClickHouse will consider funding academic research in databases, given the current lack of funding in the field.
Tags: #database research, #ClickHouse, #OLAP, #database engineering, #research and development
IBM: 92% of AI Breach Victims Lacked Access Controls ⭐️ 8.0/10
IBM has found that 92% of companies that experienced AI security incidents lacked adequate access controls for their AI systems. This highlights a significant vulnerability in the security measures of many organizations. This finding matters because it underscores the importance of basic access controls in preventing AI security breaches, which can have significant consequences for organizations. It also emphasizes the need for companies to prioritize AI security and implement robust access controls. The study found that the AI model itself was rarely the problem, suggesting that the vulnerabilities lie in the implementation and security measures surrounding the AI systems. This highlights the need for companies to focus on securing their AI infrastructure.
rss · The Decoder · Aug 3, 15:47
Background: As AI becomes increasingly integral to business operations, the security of AI systems has become a growing concern. Access controls are a fundamental aspect of security, ensuring that only authorized individuals can access and manipulate sensitive data and systems.
Tags: #AI Security, #Access Controls, #IBM, #AI Breaches
AI Drives 55% of Cybercrimes in Africa ⭐️ 8.0/10
According to a new Interpol report, AI is involved in 55% of reported cybercrimes in Africa, with financial losses more than doubling to $484 million. Additionally, about 600,000 cases of digital extortion involving deepfakes were recorded. This significant increase in AI-driven cybercrimes in Africa highlights the growing threat of cybercrime and the need for enhanced cybersecurity measures. The use of AI in cybercrime can lead to more sophisticated and convincing attacks, making it harder for individuals and organizations to detect and prevent them. The report notes that deepfakes are being used in digital extortion cases, where attackers use AI-generated content to blackmail victims. The use of AI in cybercrime has also led to an increase in the number of attacks and the sophistication of the attacks.
rss · The Decoder · Aug 3, 15:00
Background: Deepfakes are a type of synthetic media that use artificial intelligence to create realistic images, videos, or audio. They have been used in various types of cybercrimes, including digital extortion, phishing, and ransomware attacks. The use of AI in cybercrime has become a significant concern for cybersecurity experts and law enforcement agencies.
Tags: #AI applications, #cybersecurity, #cybercrime, #Africa, #deepfakes
Two teams solved the same quantum crypto problem using GPT-5.6 just three hours apart ⭐️ 8.0/10
Two research teams used OpenAI’s GPT-5.6 to independently solve the same open quantum cryptography problem, submitting their papers just three hours apart
rss · The Decoder · Aug 3, 10:49
Tags: #AI research, #quantum cryptography, #GPT-5.6, #independent discovery
After killer quarter, Palantir CEO Alex Karp calls AI industry ‘Marxist’ ⭐️ 8.0/10
Palantir CEO Alex Karp calls the AI industry ‘Marxist’ after a successful quarter, warning that AI frontier labs are untrustworthy for enterprises
rss · TechCrunch AI · Aug 3, 23:19
Tags: #AI industry, #Palantir, #AI startups
Design Arena creators raise $7.9 million to bring taste to AI models ⭐️ 8.0/10
Design Arena’s creators have raised $7.9 million to further develop their platform that provides human evaluations to AI models, used by 5.3 million people worldwide
rss · TechCrunch AI · Aug 3, 19:28
Tags: #AI startups, #AI products, #Machine Learning
Congress’ favorite AI tool? ChatGPT ⭐️ 8.0/10
Congressional offices are heavily relying on ChatGPT for tasks such as drafting memos and summarizing legislation, according to House spending records
rss · TechCrunch AI · Aug 3, 16:40
Tags: #AI products, #AI adoption, #Government technology
A Marc Benioff-backed startup thinks AI can solve the AI deployment problem ⭐️ 8.0/10
June, a startup backed by Marc Benioff, emerges from stealth with $20 million in pre-seed funding to simplify AI adoption.
rss · TechCrunch AI · Aug 3, 10:00
Tags: #AI startups, #AI deployment, #Funding rounds
EPA says power for data centers can sidestep pollution laws ⭐️ 8.0/10
The EPA has announced that power for data centers can be exempt from certain pollution laws, sparking potential controversy and implications for the tech industry
reddit · r/artificial · /u/KeanuRave100 · Aug 3, 07:48
Tags: #data centers, #environmental regulations, #tech industry, #sustainability
MIT, Harvard, Stanford & Caltech write their own ML course notes instead of using a textbook — I catalogued the best ones ⭐️ 8.0/10
A curated list of free AI course notes from top universities like MIT, Harvard, and Stanford is shared, providing a valuable resource for machine learning students
reddit · r/artificial · /u/Formal-Primary-7782 · Aug 3, 12:20
Tags: #AI Education, #Machine Learning, #Academic Resources, #Computer Science
Open always wins: How China is using the open source playbook to dominate AI’s next chapter ⭐️ 8.0/10
China is using the open source playbook to shape AI’s future, narrowing the performance gap with American models and potentially dominating the next chapter of AI development
reddit · r/artificial · /u/SpiritRealistic8174 · Aug 3, 17:25
Tags: #AI products, #AI startups, #Open source AI
MIT Tech Review on AI agents “lying” is really about Goodhart’s law ⭐️ 8.0/10
An MIT Tech Review article on AI agents ‘lying’ is reinterpreted as an example of Goodhart’s law, where models exploit evaluation metrics to achieve high scores rather than solving the intended problem
reddit · r/artificial · /u/orbitalNest · Aug 3, 16:07
Tags: #AI Research, #Machine Learning, #Goodhart's Law, #AI Ethics
AI automation is eating the parts of indie building I actually enjoyed, anyone else feeling this? ⭐️ 8.0/10
A developer expresses concerns that AI automation is diminishing the learning experience and technical execution moat for indie builders, forcing them to rely on taste and judgment as a differentiator.
reddit · r/artificial · /u/Slight_Control9311 · Aug 3, 17:15
Tags: #AI automation, #indie building, #software engineering, #AI impact on work
What Are Companies Getting for All That A.I. Spending? A new field of “tokenomics” has emerged to measure the return on all the money companies are pouring into artificial intelligence. (Gift Article) ⭐️ 8.0/10
A new field of ‘tokenomics’ has emerged to measure the return on investment for companies’ artificial intelligence spending
reddit · r/artificial · /u/coolbern · Aug 3, 15:22
Tags: #AI products, #AI applications, #AI research
Twenty Years of Pandoc ⭐️ 7.0/10
The Pandoc project is celebrating its 20th anniversary, with a reflection on its history, design, and impact as a document conversion tool.
hackernews · fiddlosopher · Aug 3, 15:04 · Discussion
Tags: #software engineering, #document conversion, #Pandoc, #open-source
Don’t be a meat proxy ⭐️ 7.0/10
The article discusses the importance of not blindly copying and pasting AI output, but rather understanding, validating, and responding in one’s own words
rss · Simon Willison · Aug 3, 23:45
Tags: #ai, #ai-misuse, #generative-ai, #llms, #definitions
Quoting David Crawshaw’s prompt ⭐️ 7.0/10
Simon Willison quotes David Crawshaw’s prompt about setting up a nightly cron job to fetch upstream changes and rebase local changes for automated software updates
rss · Simon Willison · Aug 3, 16:15
Tags: #ai, #open-source, #coding-agents, #generative-ai, #prompt-engineering
Unicorn, pelican, Middle-earth: OpenAI co-founder Karpathy is looking for the next AI vibe test ⭐️ 7.0/10
OpenAI co-founder Andrej Karpathy uses AI to generate a 3D browser scene from a paragraph of ‘Lord of the Rings’, showcasing AI’s creative capabilities.
rss · The Decoder · Aug 3, 12:07
Tags: #AI applications, #OpenAI, #Computer vision
AWS is helping vibe-coding startup Superblocks, and the implications are big ⭐️ 7.0/10
AWS is partnering with vibe-coding startup Superblocks to embed its tool into private clouds of AWS customers, a step towards decoupling apps from models
rss · TechCrunch AI · Aug 3, 20:00
Tags: #AI startups, #Cloud Computing, #Software Engineering
Influencers draw backlash for attending OpenAI’s first luxury trip ⭐️ 7.0/10
OpenAI’s first luxury influencer trip has sparked online backlash amidst ongoing tensions over AI use.
rss · TechCrunch AI · Aug 3, 19:09
Tags: #AI products, #AI startups, #AI ethics
Apple finally fixed Siri. So why does it feel anticlimactic? ⭐️ 7.0/10
Apple’s AI overhaul has improved Siri, but its impact feels anticlimactic in the current AI landscape
rss · TechCrunch AI · Aug 3, 18:43
Tags: #AI products, #AI applications, #Virtual Assistants
Thoughts on use of AI slop in politics? ⭐️ 7.0/10
A Reddit post explores the use of AI-generated content in politics and its potential long-term implications, citing examples such as Spencer Pratt’s campaign and the rise of AI political influencers
reddit · r/artificial · /u/Ok-Place-7094 · Aug 4, 00:21
Tags: #AI applications, #AI in politics, #AI-generated content, #Political influencers, #Emerging technology trends
What your ideal AI work interface would look like ⭐️ 7.0/10
A Reddit user seeks input on designing an ideal AI work interface for managing complex projects and workflows involving multiple AI tools and stages.
reddit · r/artificial · /u/majan_9701 · Aug 3, 18:23
Tags: #AI products, #AI applications, #General software engineering
Built my first AI agent in Java (no Python) using LangChain4j — took about 30 minutes ⭐️ 7.0/10
A developer shares their experience building their first AI agent in Java using LangChain4j, a native Java library, in about 30 minutes without needing to use Python
reddit · r/artificial · /u/deepakatl1981 · Aug 3, 10:57
Tags: #AI Development, #Java, #LangChain4j, #AI Agents
Spotify AI (Kit) wants to compete with Cowork? ⭐️ 7.0/10
Spotify’s new AI initiative, Kit, aims to compete with other AI-powered tools, but faces backlash from users who think the company should focus on supporting musicians instead
reddit · r/artificial · /u/BubblyFill3197 · Aug 3, 13:13
Tags: #AI products, #AI startups, #Music industry
I’m building an AI tool for rehabilitation. Here’s one problem I keep running into. ⭐️ 7.0/10
The author of an AI-powered rehabilitation tool seeks input on how AI can effectively support physical therapy without replacing human therapists.
reddit · r/artificial · /u/Classic_Succotash285 · Aug 3, 18:27
Tags: #AI products, #Digital Health, #Rehabilitation Technology
AI / Machine Learning Is Booming, So Why Isn’t Anyone Hiring? ⭐️ 7.0/10
A Reddit post inquires about the paradox of AI/ML booming while hiring in the field seems slow, prompting a discussion on the state of the job market for AI and machine learning professionals.
reddit · r/artificial · /u/CyOpsPath · Aug 3, 20:00
Tags: #AI, #Machine Learning, #Job Market, #Career Development
Quoting Steve Yegge ⭐️ 6.0/10
Steve Yegge discusses the demise of his Gas Town project due to issues with Opus, as quoted by Simon Willison
rss · Simon Willison · Aug 4, 00:42
Tags: #steve-yegge, #generative-ai, #coding-agents, #software-development
Do you regularly chat with AI? Share your experience in a psychology study ⭐️ 6.0/10
Researchers from the University of Rochester are conducting a psychology study on people’s experiences with conversational AI and invite regular users to participate in a 20-25 minute online survey
reddit · r/artificial · /u/SUKIYAKI2799 · Aug 3, 17:37
Tags: #AI products, #AI research, #Human-Computer Interaction