你的第一个AI程序员！Cognition发布Devin！程序员真的要被AI取代？
TLDRCognition, a startup that raised $20 million in Series A funding, has garnered attention with its product aimed at redefining the role of AI in software engineering. Their demo showcases an AI software engineer that assists in coding, debugging, and deployment, with a reported 43.8% success rate on the SWE bench. The discussion revolves around the potential of AI to replace human programmers, suggesting that while AI can automate routine tasks, complex problem-solving and creativity in programming may remain a human domain for the foreseeable future.
Takeaways
- 🚀 Cognition, an AI product, gained significant attention on social media on March 12, 2024, due to their A-round funding announcement of $20 million led by Stripe's founder and participation from renowned VCs.
- 🎥 Cognition released demo videos of their product, which is not yet publicly available, sparking interest in the concept of the 'first AI software engineer' and the potential of AI to replace human programmers.
- 🤖 The product interface includes a dialog box for user input and a reasoning and action (React) step display, allowing users to guide the AI through problem-solving processes.
- 🔍 Cognition's product is capable of automatically debugging and assessing whether a problem has been solved, with the potential to run and display results in various formats like web pages or command lines.
- 📈 The company claims that their AI, named Devon, achieved a 43.8% completion rate on the SWE bench, indicating a promising performance compared to other products in the market.
- 📚 The technical article from Cognition discusses how the AI programmer learns unfamiliar technologies, deploys solutions, fixes bugs, and conducts tests, with YouTube videos providing demonstrations.
- 🌐 The AI agent trend is considered the future of software development, offering a less competitive field compared to working on底层 models and infrastructure.
- 💰 The high cost of using AI agents is a concern, but the expectation is that computing power prices will decrease over time, making such technologies more accessible.
- 📊 The SW Bench test, which Cognition's product participated in, is a complex benchmark using GitHub issues and codebases to train AI models and evaluate their ability to propose solutions through pull requests.
- 🔄 The distinction between 'assisted' and 'unassisted' models in the SW Bench test highlights the challenges of AI understanding and addressing complex software engineering tasks without human guidance.
- 🔄 The concept of AI replacing programmers is discussed, with the conclusion that while AI can assist and automate certain tasks, the complete replacement of human programmers is not expected in the near term, especially for complex and creative problem-solving.
Q & A
What product gained significant attention on social media on March 12, 2024?
-The product that gained significant attention was named Cognition, which attracted a lot of interest due to its funding announcement and product demo release.
How much was raised in Cognition's A round of funding, and who were the notable investors?
-Cognition raised approximately 20 million in their A round of funding, with the lead investor being the founder of Stripe and participation from several well-known venture capital firms.
What concept did Cognition introduce with their product?
-Cognition introduced the concept of the 'first AI software engineer,' which is a topic of discussion in the wake of AI's rising prominence and the question of whether AI can replace programmers.
How does the Cognition product work?
-The Cognition product works by allowing users to input a problem they want to solve. It then displays a reasoning and action process on the right side, with the ability for humans to guide and approve the AI's proposed steps, ultimately showing the results of the actions taken.
What is the significance of the SWE Bench test results for Cognition's product?
-The SWE Bench test results showed that Cognition's product, Devon, achieved a 43.8% success rate, which is considered good when compared to other products on the market, indicating its effectiveness in software engineering tasks.
What does the term 'AI agent' refer to in the context of Cognition's product?
-In the context of Cognition's product, 'AI agent' refers to an autonomous system that can perform tasks, learn, and interact with users, potentially offering new ways to approach software development and problem-solving.
What is the current state of AI in terms of replacing human programmers?
-While AI has made significant strides and can assist in coding tasks, it is still far from fully replacing human programmers, especially in complex projects and creative problem-solving that requires a deep understanding and innovation.
How does the video compare the capabilities of Cognition's Devon with other AI models?
-The video compares Devon's performance on the SWE Bench with other models like Cloud2 and GPT-4, noting that Devon achieved a higher success rate under assisted conditions, but also highlighting that the comparison may not be entirely apples-to-apples due to differences in the nature of the AI systems.
What is the role of the SW Bench in evaluating AI's capability in software engineering tasks?
-The SW Bench is a testbed that uses data from Github issues and codebases to train AI models, evaluating their ability to propose solutions and pull requests that can successfully resolve the issues, thus providing a benchmark for AI's capability in software engineering tasks.
What are the implications of the low success rate on the SW Bench for AI models?
-The low success rate on the SW Bench indicates that there is still much room for improvement in AI's capability to handle complex software engineering tasks, suggesting that AI models have a long way to go before they can fully automate such tasks.
How does the video suggest the future of AI in software engineering?
-The video suggests that AI will continue to play an increasingly important role in software engineering, potentially reaching levels of automation similar to those seen in other fields like autonomous driving, but also emphasizes that human creativity and intervention will remain crucial for complex and edge-case scenarios.
Outlines
🚀 Introduction to Cognition and AI Software Engineer Concept
The video begins with the introduction of a product named Cognition that has gained significant attention on social media on March 12, 2024. The buzz is primarily due to Cognition's announcement of a $20 million Series A funding round, led by the founder of Stripe and other notable venture capitalists. The product, though not yet publicly available, has released demo videos that have sparked interest. Cognition introduces the concept of the 'first AI software engineer,' a topic that has been widely discussed in the wake of AI's rising prominence. The video aims to explore whether AI can replace human programmers and provides an overview of Cognition's features, which include user input, a reasoning and action step-by-step process, and automated debugging. The product is compared to other AI agents like AutoGPT and Longchain, with a focus on its maturity and stability, as well as its potential to revolutionize the software engineering field.
🧠 Analysis of AI Agent Testing and Performance
The second paragraph delves into the intricacies of AI agent testing, highlighting the importance of open-source testing frameworks that allow for extensive training and evaluation. The discussion revolves around the SW Bench, a new paper submitted to ICLR2024, which serves as a benchmark for AI agents in software engineering tasks. The video explains the test's methodology, which involves using Github issues and codebases to train AI models and assess their ability to generate pull requests that resolve issues. The distinction between 'unassisted' and 'assisted' models is clarified, with the latter providing a higher completion rate. The performance metrics of the AI agent Devon are introduced, showing a 13% completion rate under assisted conditions, which is considered promising given the complexity of the task. The paragraph concludes by emphasizing the potential for AI programmers to improve and the long road ahead for AI in software engineering.
🤖 The Future of AI Programmers and Their Impact
The final paragraph discusses the potential future of AI programmers and their role in the software development process. It suggests categorizing AI capabilities into levels, similar to autonomous driving levels, to understand the extent of human intervention required. The video acknowledges the maturity of AI technologies like GitHub Copilot, which assists in code writing, but also points out the challenges in achieving full automation in code generation, especially for complex projects. The video asserts that AI is unlikely to replace programmers in the near term, as human creativity and problem-solving in unique scenarios are beyond current AI capabilities. The content concludes with a call to action for viewers to support the video channel through likes, shares, and subscriptions.
Mindmap
Keywords
💡Cognition
💡AI software engineer
💡Financing
💡Demo video
💡React, Reasoning, and Acting
💡SWE Bench
💡AI Agent
💡Cloud2
💡GitHub
💡Oracle
💡GPT-4
💡Devon
Highlights
Cognition, a product that gained significant attention on social media on March 12, 2024, due to its A-round funding announcement of $20 million led by Stripe's founder and participation from well-known VCs.
Cognition introduced the concept of the 'first AI software engineer,' sparking discussions on whether AI can replace programmers.
The product demo showcased a user interface where users input a problem and the AI provides reasoning and action steps, with the ability for human guidance and approval.
Cognition's AI can automatically debug and assess whether a problem has been solved, offering a preview of its capabilities before full public release.
The product is based on a mature and stable architecture similar to Microsoft's AutoGPT and React, Reasoning, and Acting models.
Cognition's AI programmer, named Devon, claims to have a 43.8% success rate on the SWE bench, outperforming other products in the market.
The SWE bench is a new benchmark for evaluating AI in software engineering, using data from GitHub issues and codebases.
The test bench includes both unassisted and assisted models, with the latter providing guidance on which files to modify.
Cloud2 achieved the best results on the test bench with a 4.8% completion rate, indicating the potential for further improvements and developments.
Devon's 14% completion rate under assisted conditions suggests a challenging benchmark but does not clarify whether it's an agent or a trained model.
The discussion on whether AI programmers can replace human programmers is compared to the levels of autonomy in self-driving cars, with current AI tools like GitHub Copilot being at a Level 2.
AI's ability to write code全自动 is still challenging, especially for complex projects with strong inter-file dependencies.
The video emphasizes the importance of open-source testing and benchmarking, which facilitate training and evaluation of AI models.
The video suggests that AI programmers like Devon are the future, but the technology is still evolving and has not yet reached full autonomy in coding.
The video encourages viewers to engage with the content by liking,收藏,转发, and subscribing to the channel.
The video concludes that while AI has made significant strides, it is unlikely to fully replace programmers in the near term, especially for creative or complex tasks.
