🧑💻 Phind.com is a new search engine based on large language models that not only provides relevant search results but also generates relevant answers dynamically using either the Phind or GPT-4 model. It is specifically tailored to coders and also provides coding features like “Pair Programmer” that can help you reach higher levels of efficiency.
Thanks to the underlying open-source
CodeLlama-34B, Phind now defaults to this swift model, delivering high-quality answers to tech queries in just 10 seconds.
The model, fine-tuned with an additional 70B+ tokens, garners a HumanEval score of 74.7%, although real-world feedback shows it outperforming GPT-4 in practical helpfulness.
Notably, Phind’s speed is attributed to the use of the new TensorRT-LLM library from NVIDIA on H100s, achieving a 5x speedup over GPT-4. It also boasts a large context capacity of 16k tokens, allowing for 12k token inputs on the website, reserving 4k for web results.
💡 Although there’s room for improvement in consistency, some coders on the Phind Discord server actually prefer using Phind over GPT-4 due to its speed and helpfulness. I don’t think I’d go that far but the project is very powerful indeed.
User feedback further enriches this narrative. One user emphasized Phind’s readiness to recommend specific libraries and provide sample code, alongside offering a wealth of relevant sources like GitHub and StackOverflow, which is seen as a major advantage for further research.
Beyond Traditional Search – AI-Powered Insights
Phind AI goes beyond traditional search engines by offering a customized search experience. Users can tailor their search preferences, enabling the platform to deliver highly personalized and efficient results. Phind AI streamlines the search process and provides targeted information, specifically tailored to developers like us.
You can also use the “advanced search” that allows for additional context where you can put your code, for instance:
Currently, the search engine provides two models, i.e., Phind and GPT-4. The latter with limited availability as its still proprietary and premium at the time of writing:
The Pair Programmer feature makes the search engine more conversational and it’ll ask more detailed questions to clarify your specific information need. Truly next-level search!
If you ask it to give you code, it provides a button to copy and paste the code and also to directly run the code in Repl.it:
Phind AI harnesses specialized algorithms that cater to the intricacies of coding languages and developer queries, focusing on context and precision chatgptapi.org. This ensures that when you’re looking for code-related solutions, Phind AI offers great accuracy.
Competitors of Phind AI
Phind AI provides a unique approach to catering to developers. However, there are several competitors in the market that also leverage AI to enhance search experiences. These competitors, while not specifically tailored for developers, offer AI-driven features that could potentially be adapted for a developer-centric platform.
You.com is an AI-powered search engine that provides users with a customized search experience. It uses AI to understand user intent and deliver relevant results. While it’s not specifically designed for developers, its AI capabilities could be adapted to provide more precise results for code-related queries.
Phraser is an AI tool that appears to be a search engine for digital art collections. It uses keywords to find relevant images. Although it’s not directly related to code or developer queries, its AI-driven image search capabilities could be adapted to search within code repositories or developer forums.
ChatGPT is an AI model developed by OpenAI that uses language models to generate human-like text based on the input it’s given. While it’s not a search engine per se, its AI capabilities could potentially be used to enhance the search experience by providing more detailed and relevant results.
I still use ChatGPT because personally I believe GPT-4 with DALL-E, image recognition, and Bing URL plugins, it’s the best AI tool ever created by humanity.
Frequently Asked Questions
How does Phind AI tailor its search experience to developers?
Phind AI tailors its search experience to developers by understanding the unique requirements of each developer. Users can personalize their search preferences, enabling the platform to deliver highly personalized and efficient results. You have code execution capabilities and a model fine-tuned with coding related tasks. This is achieved by leveraging artificial intelligence algorithms that focus on context and precision in coding-related search, generation, and debugging tasks.
How does Phind AI provide AI-driven insights?
Phind AI provides AI-driven insights by not only delivering relevant search results but also offering suggestions and related topics. This comprehensive approach ensures that developers have access to a wealth of information, allowing them to explore various angles and gain a wider perspective. This is achieved by leveraging large, proprietary AI language models based on CodeLlama.
🧑💻 Recommended: Code Llama 2: Examples and Playground (Try It Yourself)
How does Phind AI help developers find relevant information quickly?
Phind AI becomes the go-to resource for developers searching for specific information. It saves valuable time and effort by quickly and effectively finding information across various subjects, including code snippets, documentation, tutorials, and more. This efficiency enhances developers’ productivity, allowing them to focus on their core tasks.
How does Phind AI assist programmers in their learning journey?
Phind AI offers more than just search results – it provides AI-driven insights that keep programmers updated with the ever-evolving tech landscape. From discovering new frameworks, languages, or tools to understanding best practices and industry trends, Phind AI becomes a trustworthy companion that assists programmers in their constant learning journey.
🧑💻 Recommended: Code Llama 2: Examples and Playground (Try It Yourself)
Prompt Engineering with Llama 2
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You’ll delve into practical applications such as book PDF querying, payroll auditing, and hotel review analytics. These aren’t just theoretical exercises; they’re real-world challenges that businesses face daily.
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While working as a researcher in distributed systems, Dr. Christian Mayer found his love for teaching computer science students.
To help students reach higher levels of Python success, he founded the programming education website Finxter.com that has taught exponential skills to millions of coders worldwide. He’s the author of the best-selling programming books Python One-Liners (NoStarch 2020), The Art of Clean Code (NoStarch 2022), and The Book of Dash (NoStarch 2022). Chris also coauthored the Coffee Break Python series of self-published books. He’s a computer science enthusiast, freelancer, and owner of one of the top 10 largest Python blogs worldwide.
His passions are writing, reading, and coding. But his greatest passion is to serve aspiring coders through Finxter and help them to boost their skills. You can join his free email academy here.