Fidens Simanjuntak’s Post

The best LLM use cases are where you use LLM as a tool rather than expose it directly. As Richard Seroter says, how many chatbots do you need? However, this use case of replacing static product pages by personalized product summaries is like many other LLM use cases in that it faces unique risks due to non-determinism. Imagine that a customer sues you a year from now, saying that they bought the product because your product summary claimed (wrongly) that the product was flameproof and their house burned down. The only way to protect yourself would be to have a record of every generated summary and the storage costs will quickly add up ... One way to avoid this problem (and what I suggest) is to generate a set of templates using LLMs and use an ML model to choose which template to serve. This also has the benefit of allowing human oversight of your generated text, so you are not at the mercy of prompt engineering. (This is, of course, just a way to use LLMs to efficiently create different websites for different customer segments -- the more things change, the more they rhyme with existing ideas). Many use cases of LLMs are like this: you'll have to reduce the non-deterministic behavior and associated risk through careful architecture.

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Build an AI Sales Bot $$$ using YOUR INVENTORY! GPT-4o Nextjs SingleStore Step 1: Sign up here to follow along >> https://msql.co/ania-kubow Step 2: Watch the tutorial over on my YouTube channel! This video has been a long time in the making and I am so happy it is finally here! If you have ever wanted to build an app that will help you make sales calls based on your shop data, that is exactly what we are going to be building today. Users will be able to pick multiple options they are interested in, input their phone numbers, and an AI sales bot will given them a call and suggest an item from your shop database. The goal of this app is for you to pick up leads that will actually want to buy something. So have the AI entice and filter out actual keen users before they actually get to speak to you. Of course this is just an example app, based on my furniture shop inventory. Once completing this app, you can use what we learn today and the template, to cater it towards your specific business needs! So have an AI that suggests real estate properties maybe, or simply cold calls a list of potential leads you already have. The world of possibilities is endless and I would absolutely love to see how you take this app, build on it, and make it your own!! Please do share yours with me when you are done because I would love to see what business case you came up with. https://lnkd.in/dUdcZFDD

What does the release of`gpt-4o-mini` mean for those developing AI apps? 👉 This from the perspective of my text-mining app which helps you find insights from user reviews, customer surveys, etc. =============== What's the big deal? =============== ✅ gpt-4o-mini is a FASTER version of gpt-4o. ✅ gpt-4o-mini is CHEAPER than gpt-3.5-turbo (60% cheaper!). ❌ gpt-4o-mini is not as good as gpt-4o for complex tasks. ================== So, what does this mean? ================== 💡 Where my app was using 3.5-turbo, switch to 4o-mini 💡 Where my app uses 4o--Can make the switch to benefit from performance gains without impact to accuracy. ============================ THE biggest benefit of the new model ============================ Reflective prompting just got a WHOLE lot cheaper! ℹ Reflective prompting is where you get the LLM to double-check its own output. This improves accuracy! My view: The price drop and performance improvements means that reflective prompting has now a major part of AI development. But a lot of testing needs to be done to validate accuracy using reflective prompts. 🙄 My plans for today has suddenly changed. But, so far my testing with reflective prompting is looking very promising indeed! (I know, I'm not talking much about experimentation lately, but I will get back to it, I promise! 😂 ) #ai #userresearch #cro

5 Best Free AI Tools For Web/App Developers in 2024!💻 1️⃣ TensorFlow.js: Revolutionize your web apps with client-side AI! Train and deploy machine learning models directly in the browser, no server needed. 🤖🌐 2️⃣ Microsoft Lobe: Build custom AI models effortlessly with a drag-and-drop interface. Perfect for image classification and beyond, simplifying AI integration for web and mobile apps. 🎨🔧 3️⃣ Hugging Face's Transformers: Elevate your app with cutting-edge NLP models for text generation, translation, and more. Enhance user interactions with advanced AI-driven capabilities. 📝💬 4️⃣ GitHub Copilot: Boost coding efficiency with AI-powered suggestions and smart completions. Write code faster and smarter, reducing errors along the way. 💻⚡️ 5️⃣ Dialogflow: Craft intelligent chatbots and voice assistants effortlessly. Seamlessly integrate natural language understanding into your apps for superior user engagement. 🗣️🤝 Embrace the future of development with these powerful AI tools! 🌟 Which one will you integrate into your next project?! 💼✨ Tell me in the comments!💬💡 #AyyanAliBhati #AI #AITools #WebDevelopment #AppDevelopment #freeAItools #AItoolsforwebandappdevelopers #aitoolsforcoding #AItools #TensorFlow #MicrosoftLobe #HuggingFace #GitHubCopilot #Dialogflow #AI #artificialintelligence

There hasn't been much buzz around AI until Sam Altman announced the launch of OpenAI in 2022. But little did we know that single announcement would change the game for businesses and software development. It's been a crazy ride ever since, with more innovative AI uses and models popping up left and right. Since OpenAI's launch, the big players have been jumping on the AI bandwagon. Google's got Gemini, Microsoft's got Co-pilot, and Facebook's got Meta AI - the list goes on. And it's not just about the tech giants. AI is becoming the new normal for businesses and operations. Just throw an AI model into your software, and voilà! Instant autopilot. It's no secret that AI is the new gold. And last week's Google I/O '24 conference was all about it. AI was the star of the show, with Gemini making waves in search, music, videos, images, and more. And then there's Devin, the new coding assistant, making us wonder if AI will replace developers (share your thoughts on this). But here's the thing: as frontend developers, we need to stay ahead of the curve. So, how can we leverage AI to our advantage? I've got two ideas to get you started: 1. Learn to build with AI: Learn to incorporate AI models into your projects to automate tasks, enhance user experiences, and stay competitive. 2. Learn the basics of AI: Understand the fundamentals of AI to effectively integrate it into your work and stay invaluable. AI is the future, and it's time to embrace it. Let's make the most of this exciting technology and stay ahead of the game. ©William Anaza Frontend Developer / Website Designer

Artificial intelligence (AI) and machine learning (ML) are revolutionizing mobile app development in today’s fast-paced digital landscape. Understanding the technical intricacies of AI and ML is crucial for developers and businesses alike. This knowledge not only helps in making informed decisions but also in leveraging these technologies to their full potential. This article delves into the technical aspects of AI and ML in mobile apps, exploring the technologies, algorithms, and frameworks that drive their development along with key differences between AI vs Machine Learning, Generative AI vs Machine Learning.

🚀 The Unseen Wave: AI's Disruption & the Strategic Imperative This weekend, Simon Gray's reflections illuminated the art of strategic thinking, exemplified by Sir George Cornewall Lewis's adept handling of British diplomacy during the American Civil War (link in comments below). His strategic insight prevented grave miscalculations in British foreign policy and, in particular, British recognition of the independence of the Confederacy (potentially changing the course of history). Equally profound are my recent encounters with AI capabilities, demonstrated by ChatGPT designing a Figma wireframe in seconds (below)—a task traditionally demanding significant human effort, time, and skill. UX and UI developers, often command large six-figure salaries (much like City lawyers) but highly skilled software development jobs are as much at risk as investment banking, management consultancy and legal roles going forward. The legal industry still appears to be an ostrich with its head firmly in the sand, unaware of the looming transformation. As Hill and Gerras recommended in the article below, leaders must adapt to this changing landscape by: > Conducting Thought Experiments: Anticipate and prepare for strategic anomalies. > Avoiding Expertise Tyrannies: Challenge entrenched expertise within organisations. > Creating Variance Space: Allow for both planned and unplanned deviations in strategy. > Seeking Experimental Results: Pursue unexpected outcomes and insights. > Revising Orthodoxy: Update or replace outdated strategies and assumptions. > Transforming Culture: Cultivate an organisational culture that embraces continuous change and innovation. These steps are vital as AI redefines traditional roles and operations, demanding a shift from conventional strategic planning to dynamic, proactive strategic thinking. For senior legal professionals, particularly Managing Partners, recognising and adapting to these shifts is not merely an option but a necessity. From my conversations over the past two years, I am highly skeptical that the magnitude of this shift has truly registered. #AI #LegalTech #StrategicThinking #DigitalTransformation #Innovation #Figma

Artificial intelligence (AI) and machine learning (ML) are revolutionizing mobile app development in today’s fast-paced digital landscape. Understanding the technical intricacies of AI and ML is crucial for developers and businesses alike. This knowledge not only helps in making informed decisions but also in leveraging these technologies to their full potential. This article delves into the technical aspects of AI and ML in mobile apps, exploring the technologies, algorithms, and frameworks that drive their development along with key differences between AI vs Machine Learning, Generative AI vs Machine Learning.

AI isn't here to steal your job… yet. It's your new power-up, the ultimate jack-of-all-trades assistant, ready to make you sharper, faster, and more creative. Take coding, for instance... I remember spending hours crafting a complicated react component from scratch. With AI, it can be done in minutes. And gone are the days of drowning in API docs. I recently built a software tool with an API I'd never touched before – something that would've taken weeks, only took me a day. ai frees us from the mundane, letting us focus on the truly innovative stuff. It's like going from pen and paper straight to photoshop. Embrace the change, and you'll unlock a whole new level of output. Or resist, and risk getting left behind. So, what are you using AI for? Do you have any cool examples where it saved the day (or a just few hours)? #ai #ecommerce #webdevelopment