Toptal’s Post

A deep dive into the pros and cons of AI generated code. Recent advances in prose-to-code generation via Large Language Models promise a shift towards "programming in prose" for non-programmers. This methodology enhances comprehension and cuts code errors, but traditional testing remains crucial. How will this synergy of high-level languages and #AI reshape the future of #programming? Read more: https://accntu.re/3EaIin1

Artificial intelligence adoption has exploded over the past four (4) years, especially since OpenAi’s ChatGPT was released; and a wealth of organizations across industries have reported plans to expand their AI strategies this year. This digital transformation has sparked a growing demand for AI practitioners. In fact, AI-related hiring increased by 165% between 2020 and 2021. AI has the capacity not only to optimize operational processes, but to create innovative business models, products, and services—which is why a majority of business leaders feel positive about the future impacts of AI. However, for businesses who are planning on adopting AI, before selecting an AI language for development projects, they should outline their project’s goal and deliverables. Assess the tasks at hand and identify the resources required to complete them. Next, consider the tools and libraries associated with each AI programming language and decide which language is best suited to meet the needs of your project. Mainstream languages like Python, Java, and C++ are often popular choices for beginners, but there are more robust ones. Whatever you choose, be sure to carefully weigh the unique advantages and limitations afforded by each in the context of what you seek to accomplish.

What is OpenAI code interpreter, and how does it work?: Discover the OpenAI code interpreter, an AI tool that translates human language into code. Learn about its functions, benefits and drawbacks in this guide.

> Generative AI is helping to meet people partway by greatly expanding the ability of computers to understand us. But it’s still on us to learn how to be understood. Over the weekend, ChatGPT helped me create a web application using Python, Anvil, OpenAI, and Tavily. Without assistance, it would have easily taken me two weeks...at least. That said, the responses from ChatGPT were full of hallucinations. The AI will confidently create code that draws on methods that don't exist. It will write code based on natural language prompts but not necessarily code that achieves your objectives. Clear and precise English is essential but it's not sufficient. In other words, generative AI is great at creating what my business partner, Laura Black, calls "ugly first drafts." Turning UFD's into final product still takes human know-how. Nevertheless, the value of generating a (not-so) ugly first draft fast should not be underestimated. Getting a "pretty good" fast start can help make the difficult achievable and the "impossible" merely difficult. https://lnkd.in/gGEZfcax

It looks like we have serious competition in AI world. Meta introduced Code Llama, an AI tool for coding and SeamlessM4T speech to speech / text translator for 100 languages. Looks really impressive. It will be interesting to check if Code Llama is more advanced than ChatGPT from the coding perspective. Do developers need to consider how to adjust their jobs in the face of AI competition? #AICompetition #ArtificialIntelligence #TechInnovation #AIChallenges https://lnkd.in/g552gxy8 https://lnkd.in/gQUC3eqN

[#LangChain] Unlocking the Power of AI Development! 💡LangChain is a state-of-the-art, freely available tool created to help app developers utilize large language models (LLMs) in the creation of AI powered applications. Do you want to create an application like this easily? Read on 🔽 #AI #Development #LLM

Code Llama: the AI programming assistant with the best resume Meta has released Code Llama, a set of AI models suitable for assistance in programming. It is based on the wildly popular open-source model Llama 2. Meta boasts some impressive #results from AI benchmarks: is Code Llama the best coding assistant? In the scientific paper, Meta researchers talk about the rapid evolution that #llms (large language models) have undergone. A chatbot like ChatGPT can provide stunningly credible answers to all sorts of questions. What is missing there, however, is accuracy: despite the huge number of parameters (reportedly over one and a half trillion), an LLM can make many mistakes. A more compact, theoretically less sophisticated AI model can still be significantly more useful for specific tasks with a high-quality #dataset. Code Llama is a further development of the Llama 2 model, and is specifically trained on programming code and its documentation. Depending on the specific variant, it may supplement, generate or explain computer language based on user input. It may be used just like Llama 2: that is, it’s available for commercial purposes as well. https://loom.ly/3mZI3ks

🚀 Introducing DSPy: The Future of Foundation Model Programming The tech world is abuzz with a groundbreaking development that promises to redefine the way we interact with AI, particularly Large Language Models (LLMs). Stanford NLP's DSPy framework is pioneering a shift from manual prompting to a more robust, programming-centric approach for foundation models. 🔧 Solving the Fragility Problem Building applications with LLMs has always been a balancing act, requiring intricate prompt engineering to achieve desired outcomes. However, this process is notoriously fragile; a minor change in the pipeline or data could necessitate a complete overhaul of prompts or fine-tuning steps. DSPy emerges as a solution to this challenge, offering a way to recompile the entire pipeline systematically, optimizing it for specific tasks without repetitive manual adjustments. 💡 DSPy: Beyond Prompting to Programming DSPy stands out by emphasizing programming over prompting, moving the construction of LM-based pipelines closer to traditional programming practices. This paradigm shift is aimed at making the development process more systematic and powerful. By decoupling the program flow from the parameters of each step and introducing new optimizers driven by LMs, DSPy enables fine-tuning prompts and weights with unparalleled precision, catering to the specific metrics you aim to maximize. 🚀 The Impact on Data Engineering and AI Development DSPy's approach facilitates the creation of more reliable tasks, enhancing quality and avoiding specific failure patterns associated with LLMs. It represents a new era where the complexities of LLMs and their prompts become manageable components of a larger, self-improving system that learns from data. This means less time spent on prompt engineering and more focus on achieving higher scores and more efficient solutions. 👩💻 For Developers and Engineers: A Call to Action The introduction of DSPy invites developers and data engineers to embrace a new set of tools and methodologies. By leveraging general-purpose modules and optimizers provided by DSPy, professionals can replace string-based prompting tricks with a more structured and scalable programming model. This not only streamlines the development process but also opens up new avenues for innovation in AI-driven applications. Embracing the DSPy Framework: The Road Ahead As we stand on the brink of this transformative era in AI and data engineering, DSPy offers a glimpse into a future where programming with foundation models becomes as intuitive and flexible as working with conventional software. The potential for DSPy to revolutionize AI integration and application development is immense, heralding a new chapter of opportunities for the tech community. ☛ https://lnkd.in/d2MRd-kM #AI #DataEngineering #Programming #FoundationModels #DSPy #StanfordNLP #TechnologyInnovation #llm

Meta has just introduced "Code Llama, an AI Tool for Coding" - free for research and commercial use. The competition in the field of generative AI is heating up for sure. Read more on https://lnkd.in/e4sZNNKZ. #meta #airesearch #codegeneration #generatieveai #codellama #llama2 #largelanguagemodel #artificialintelligence

What is OpenAI code interpreter, and how does it work?: Discover the OpenAI code interpreter, an AI tool that translates human language into code. Learn about its functions, benefits and drawbacks in this guide.