Digital Tails Group的动态

???????? ?????? 5 ???? ???????????? ?????? ???? 2 ??????????..... ???????? ???? ???????????????????? ???? ???????? ???? ??????. Open AI is set to release its latest advanced model, "Strawberry", in 2 weeks. (Many think this could be Chat GPT 5). A model that has an "advanced reasoning ability" A group of selected people already have access to test it out. According to the testing group, here are some of their thoughts on this latest model. Key Features: ? Response Time:?Strawberry takes about 10-20 seconds to reply, using built-in “Chain-of-thought” prompting for more complex reasoning. ? Text Creation Only:?Initially, it will only generate text, with no image creation capabilities yet. Pros: ? Improved performance in coding and math problem-solving. ? Better at asking clarifying questions, leading to fewer mistakes. ? Acts like a personal business strategist for subjective tasks. Cons: ? The 10-20 second response time can feel slow, even for simple queries. ? Early feedback suggests the improvements are minor, not necessarily worth the wait. ? Memory issues: It may struggle to remember previous conversations or user preferences. ? Pricing is still undecided, with potential for a new paid tier. OpenAI has explored enterprise pricing as high as $2,000, but this seems high given early reviews. ? Likely to have usage limits, which could be bypassed with a more expensive subscription—possibly in the $30 to $45 range. How good this new model actually is? I guess we'll find out in 2 weeks :) #AI #Openai #aiforbusiness

#GPT-o1 vs. #GPT-4o: Which #AI Model is Right for You? OpenAI’s new GPT-o1 model isn’t better than GPT-4o—it’s just built for different things. Here’s the breakdown: ?? GPT-o1 is a game-changer for complex tasks like math, logical reasoning, and temporal understanding. It’s designed to think through problems step-by-step—things that most AI models struggle with. But here’s the catch: GPT-o1 isn’t the best at everything! For tasks like code completion or creative writing, GPT-4o and other models might actually do better. In fact, on certain benchmarks, GPT-o1 ranks behind GPT-4o and even Claude-3.5 Sonnet! ?? Why? Because GPT-o1 takes more time (and money) to give you a well-reasoned answer. It generates more output called “reasoning tokens” to arrive at its conclusions. You probably don’t need that if you’re just having a casual conversation or simple chatbot interaction. Where GPT-o1 really shines is in complex scenarios like: “Here’s everything I know, analyze it carefully, and when you’re ready, give me a thorough answer and tell me why.” As AI gets more advanced, knowing which model to use for different tasks will be a key skill in business. GPT-o1 may not be the right tool for every job, but in the right context, it’s a total game changer. #AIInnovation #OpenAI #GPTModels #BusinessIntelligence #AIReasoning #TechTrends #AIForBusiness #FutureOfWork #DataProcessing #AIGameChanger

?? Exciting News: The Release of GPT-4o! ?? During a recent class, there's been a running joke that I'd end up like the protagonist from the movie "Her"—romantically linked to an AI. With the arrival of GPT-4o, equipped with full voice and video capabilities in real-time, that joke isn't so far-fetched anymore! A full-fledged AI assistant is now accessible to the wider public, and yes, even AI girlfriends for some. On a more serious note, yesterday's keynote announcement marks a significant milestone, as GPT-4o is set to transform industries like education, software engineering, healthcare, and more. Here are the main features: Key Features: - Enhanced Accuracy: Delivers better comprehension and text generation for more accurate responses. - Multimodal Abilities: Handles both text and images, broadening application possibilities. - Contextual Understanding: Maintains deeper context for more coherent and appropriate outputs. - Scalability: Designed for both individual users and large enterprises. Applications Across Industries: - Customer Support: Provides instant, accurate responses to customer inquiries. - Content Creation: Generates high-quality content, from articles to social media posts. - Research Assistance: Summarizes and synthesizes complex information swiftly and accurately. - Educational Tools: Offers interactive, AI-driven content that enhances learning experiences. We're excited about the endless possibilities GPT-4o offers and can't wait to see how it drives innovation across various fields. Let's embrace this new era of AI together. For more information, visit OpenAI's website. Also, good news for clients adopting AI: this version, excluding voice and image capabilities, is available for most without the need for a $20/month subscription. This means you can access custom GPTs without additional costs. Stay tuned for more updates on the implications of this in the coming days! What features of GPT-4o are you most excited about? Share your thoughts in the comments! https://lnkd.in/ewu5XyVM #ArtificialIntelligence #GPT4o #Innovation #TechNews #AI

Why AI Agents Are Not Just GPT Wrappers. The excitement around AI Agents is huge because they can make decisions, perform actions, and handle long tasks without human interaction. ? Let's first understand what GPT wrappers are. Here’s a simple example: A tool that can answer any email. To build an email answering tool, we just need to connect our interface with an LLM's API. The user can input an email with a prompt to tell the system what to do with it, and the system will display the output from the LLM in a clean interface. Suppose someone asks in an email if we can meet this Monday. The LLM could generate a response like: "Let me check my schedule, and I'll get back to you soon." The problems here are: 1. No Context: It doesn’t know whether to say yes or no to the email. 2. No External Tools: It doesn’t have access to my calendar to check if I’m free. 3. No Security: What if the email asks for private details? 4. No Boundaries: It doesn’t know how to avoid critical conversations. 5. No User Control: The user has no control over shaping the answer. 6. Hallucinations: It can make things up. ? Now, let’s learn about AI Agents and how they differ from GPT Wrappers. AI models can be chained to build workflows, where the output of one model becomes the input for the next. AI agents do not follow fixed steps, where control logic is typically handled by humans. An AI agent’s process is dynamic and adapts to each situation. Here’s an example of an email answering tool with an AI Agent: 1. Goal: The user provides an email and seeks help to come up with an answer. 2. Reason: The agent will plan, think, and break the task into smaller steps. 3. Act: It will use external tools like a calendar to check when the user is free and previous emails to understand the context. 4. Memory: It stores memory (logs or conversation history) to improve its performance over time. 5. Observe: The agent monitors each task. If something goes wrong, it replans and finds the best way to achieve the goal. 6. Output: It provides the output after successfully performing all the steps. Hope you have learned something? Are you excited about AI Agents? #mern #nextjs #ai #aiagents #job

ICYMI - GPT voice is now updated and it’s really good! I can now walk and talk about anything on my mind including deep learning. (Reposted with better instructions) ??? Knows today’s date, and it has real-time search. ? ??? Can be interrupted to shorten, steer the conversation or celebrate a spontaneous moment "with" someone. ??? Learning something new? I can walk and talk and learn about tech systems then ask “him” to quiz me. (voice selections optional) ??? Practice a #sales pitch and get evaluated by GPT. ??? Need a phone number, ask GPT vs. Google (pending phone numbers to be hyperlinked.) ??? Once the API launches, this feature will be a natural embed for #chatbots in #customerservice, smart devices, accessibility, and more! ?? Memory is being updated through the conversation, which can be deleted. For example, GPT knows I’m an #LSUTiger fan, have deer in my neighborhood and what my professional interests are. I can manage what it knows in the profile. If you've seen the movie "Her" Memory is the necessary component, along with empathy to having in-depth conversations. Today: Ask GPT anything for your personal/professional knowledge. SOON: Ask AI to do things for you. Once Apple provides AI access to apps, with permission, we will be walking down the street and ask it to order the book it just recommended. ? Not sure how to access GPT's Advanced Voice ? On your phone, download the GPT app, sign in, then click the black with white striped icon in the very bottom right of the text entry field. IF you don’t see a colored, animated globe, start a new chat and try again. The white clouds are “old tech”. Have fun - be safe - and don’t discuss any secrets you don’t want the next models to know! ?? See comments for screenshots. #AITech Susan Westwater #WhatsNext

??How Chain-of-Thought Reasoning Transforms Problem-Solving After the latest release of OpenAI models, we hear a new term in AI: Chain-of-Thought (CoT) Reasoning. So, what exactly does it mean? Imagine a model is tasked with solving a math problem, like calculating the total cost of 3 items, each priced at $10, with a 10% tax. Instead of providing a quick answer, the model uses Chain-of-Thought Reasoning, breaking the problem down into steps like this: First, calculate the total cost before tax: $10 × 3 = $30. Then, calculate the tax: 10% of $30 = $3. Finally, add the tax to the total: $30 + $3 = $33. By reasoning through each step, the model ensures it arrives at a correct and thoughtful solution. Without CoT Reasoning, the model might give a quick, one-step answer, which is more likely to be incorrect, especially for tasks requiring multiple steps. CoT Reasoning allows models to handle complex, multi-step problems more effectively, mimicking how humans approach problem-solving—one step at a time. --- ?? Follow Abdul Rahim Roni for more such content: If you like this and want to get more AI tools, tutorials and news, join Cool Tech Gadgets - my newsletter that helps you get smarter about Microsoft and AI and Google and technology: ?? https://lnkd.in/grn4UX-8 #ai #chatgpt #generativeai

?? Big news in the AI world! OpenAI just launched a new model, OpenAI 01 (not "Strawberry"), and it’s designed to reason at a PhD level. ?? What’s new? This model is available now (September 12, 2024) for all ChatGPT Plus, Teams, Enterprise users, and some developers. It’s built for reasoning—designed to go through a multi-step process, breaking down complex questions and delivering well-rounded, thoughtful answers. It’s not just speed; it’s depth. Why is this exciting? On math benchmarks, GPT-4.0 scored 13%, while OpenAI 01 hit 83%. That’s an incredible leap in capability for tasks requiring critical thinking. While it’s slower to respond, the payoff is high-quality, step-by-step reasoning that’s ideal for business owners and complex problem-solving. What’s the catch? It’s not for everyone—this model lacks GPT-4.o's ability to browse the web or work with images (it's not multimodal). But if you need precise, logical reasoning, this is a game-changer. OpenAI is continuing to evolve with upcoming updates and plans to release this model to free users. We’re witnessing a shift in AI development—inference-time scaling is now in production. Like AlphaGo's Monte Carlo Tree Search (MCTS), OpenAI 01 rolls out possible strategies, narrowing in on the best solution through repeated sampling. This approach is proving more effective than simply scaling up model parameters. But there’s more. This model isn’t just delivering better answers—it’s learning from its processes, creating a data flywheel effect. As it solves problems, it generates mini-datasets, improving the reasoning core over time. The focus now is optimizing inference computing rather than just building bigger models. This is where AI is heading, and OpenAI is leading the charge. Curious to dive deeper? Follow me for more insights and updates on AI innovation! ?? #AI #OpenAI01 #Strawberry #TechInnovation #ReasoningAI #GPT #AIResearch #LLMs #AIinference #MachineLearning #AIConsulting #AITrends

If you ask GPT 4o, “If I have 10 books and I read 2, how many do I have left?” It would say 8, but OpenAI's o1 model ( released yesterday) goes deeper: “You still have 10 books. Reading doesn’t remove them, but you now have 8 unread ones.” That’s the power of o1—it doesn't just answer, it reasons. Whether it's solving complex coding or math problems, o1 uses reinforcement learning to tackle multistep challenges. It’s also designed to reduce hallucinations, offering more accurate responses. Available through the ChatGPT Plus and API, o1 might a new standard in AI. And while "reasoning" might sound like a marketing term (as models predict rather than truly reason), o1 is a step closer to AI that thinks before it responds. For developers, the o1-mini offers a faster, cheaper alternative optimized for coding tasks. #AI #OpenAI #Tech #API #MachineLearning #Innovation

Well structured prompt. To create an effective prompt for generative AI models, understanding the nuances of prompt engineering is essential. Here’s a comprehensive guide to crafting the perfect prompt, drawing insights from leading AI companies like OpenAI, Anthropic, and Google. Understanding Prompt Engineering: Prompt engineering involves designing inputs that guide AI models to produce desired outputs. Companies like OpenAI* with its ChatGPT, Anthropic with Claude, and Google with Gemini have demonstrated the importance of well-structured prompts in enhancing AI performance. Key Elements of a Perfect Prompt: 1. Clarity: Use clear and unambiguous language. Avoid jargon unless necessary. A well-defined question leads to more accurate responses. 2. Specificity: Be specific about what you want. Instead of asking for "a summary," request "a concise summary of the key themes in Shakespeare's 'Hamlet'." 3. Context: Provide context to help the model understand the background. For example, specify the audience or purpose of the content. 4. Format Instructions: If you need the output in a particular format (like a list, essay, or dialogue), state this explicitly. For example, "List five benefits of renewable energy." 5. Iterative Refinement: Use follow-up prompts to refine the output. If the first response isn’t satisfactory, ask for adjustments or more details. 6. Tone and Style: Specify the desired tone (formal, casual, persuasive) to align the output with your needs. For instance, "Write in a friendly and engaging tone." Example of a Well-Structured Prompt: “Write a 300-word article on the benefits of meditation for mental health. Include three key benefits, use a friendly tone, and conclude with a call to action encouraging readers to try meditation.” Effective prompt engineering can significantly enhance the quality of AI-generated content. By incorporating clarity, specificity, context, format instructions, iterative refinement, and tone, users can unlock the full potential of generative AI tools. As AI technology continues to evolve, mastering prompt engineering will remain crucial for achieving optimal results. #PromptEngineering #AI #OpenAI #Anthropic #Google #GenerativeAI #ContentCreation #MachineLearning #ArtificialIntelligence #SEO

Learn how Pioneer Dev AI harnesses OpenAI to build custom Large Language Model (LLM) applications to revolutionize business operations (https://lnkd.in/gJHHxeu5). ?? Improve customer interactions with quick, accurate responses and 24/7 support ?? Transform vast amounts of data into actionable insights for better decision-making ?? Automate routine tasks to boost efficiency and reduce operational costs #AI #LLM