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Powered by ai (automated post) In the ever-evolving world of AI, it's crucial to stay updated on the latest strides and developments. Here are three captivating articles I've come across recently: The creative intersection of technology and nature has taken a fascinating turn with Matt Reed's latest innovation. He's harnessed the power of GPT-4o alongside a Raspberry Pi to enable communication with plants. Yes, you read that right. Through this setup, you can ask a Mandrake if it's feeling well – a delightful integration that's both quirky and a potential glimpse into the future of human-plant interactions. https://lnkd.in/dfmwCRWu The conversation around AI ethics remains as relevant as ever, especially with AI firms' attempts to replicate human attributes within their technologies. A recent example is the controversy surrounding OpenAI's use of Scarlett Johansson's voice approximation in GPT-4o. This event has sparked discussions on consent and control in the realm of AI and how celebrities, alongside the general public, interact with these emerging technologies. https://lnkd.in/dgUnRhkd OpenAI, a leading figure in the AI industry, has rolled out their newest conversational model GPT-4o, dubbed "omni." This update promises enriched contextual understanding and a broader application spectrum, potentially redefining the way we interact with virtual assistants. As AI becomes even more integrated into everyday technology, it’s worth exploring how this innovation will influence user experience and overall AI interaction. https://lnkd.in/duwWFbsS These articles not only showcase the inventive uses of AI but also raise important ethical questions that need addressing as we advance. As we march into this brave new world, keeping an informed and critical eye on these developments will be critical. While AI exhibits immense potential to augment our reality, it's up to us to navigate this terrain thoughtfully and responsibly. Will we rise to the occasion? Only time will tell.

OpenAI recently introduced a five-tier system to measure progress toward artificial general intelligence (AGI), their primary goal. This ranking system helps communicate internal AI milestones and aligns with societal handling of AGI's potential disruption. Currently, OpenAI's technology, like GPT-4o powering ChatGPT, is at Level 1, capable of conversational interactions. Executives indicate they're nearing Level 2, "Reasoners". OpenAI isn't alone in trying to figure out how to rank things that don't yet exist. Researchers at Google DeepMind also proposed a five-level framework to assess AI advancement. Establishing these ranking systems is crucial for benchmarking progress, ensuring transparency, and fostering innovation. At AI Native Foundation https://lnkd.in/gV4ZGTeb, we believe that such frameworks are essential for ethical AI development and modernization. Clear benchmarks allow for accurate assessment and foster collaboration, promoting responsible growth and addressing AI's broader societal implications. #AI #ArtificialIntelligence #OpenAI #AGI #RankingSystems #Innovation #EthicalAI #AINativeFoundation Danny Goh Mark Esposito, PhD Terence Tse, PhD https://lnkd.in/gZsK_ePE

No single company should ever 'own' the standard by which the market evaluates it's effectiveness... this is because being the goalkicker and goalkeeper at the same time rarely works out in the long term. That said, the #AI progress levels proposed by OpenAI (outlined below) are not that dissimilar to the AI safety levels recently published by Anthropic, and also share some level of alignment with Google Deepmind's suggested approach. Perhaps an industry consensus is near... 💥Level 1: Chatbots, AI with conversational language 💥💥Level 2: Reasoners, human-level problem solving 💥💥💥Level 3: Agents, systems that can take actions 💥💥💥💥Level 4: Innovators, AI that can aid in invention 💥💥💥💥💥Level 5: Organizations, AI that can do the work of an organization https://lnkd.in/gZsK_ePE

Many companies employ AI to generate content, but it's often easy to distinguish machine-written text. This article explores various methods to enhance the human-like quality of AI-generated text. https://lnkd.in/e_2QZNrK #insurtech #generativeai #insuranceagent #insurancebrokers

🚀 How Retrieval-Augmented Generation (RAG) is Solving AI’s Hallucination Problem 🤖 We’ve all heard about how AI can produce inaccurate or "hallucinated" information—just ask lawyer Steven Schwartz, who presented fake cases in court, thanks to GPT! 😬 In my latest article, I dive into RAG (Retrieval-Augmented Generation), a powerful technique to help AI models access real-time, relevant data and produce more accurate responses. 🔍 Discover how RAG works, its advantages, and the challenges it faces in improving AI performance. Check it out on DEV.to, and let’s discuss how this could change the future of AI. #AI #MachineLearning #RAG #GPT #ArtificialIntelligence #DataRetrieval #TechInnovation

As more and more of the content online is #AI generated less and less of it will be useful for training AIs. This will make real people-generated data more and more valuable. People interaction data will become scarce as AI-agents do most of the engagement for us. This could create a downward spiral of 'good 'AI responses, or a cliff as this study indicates. Companies that understand AI and deploy it internally to optimise for this can pivot to internal models. Those that don't will skew farther away from accuracy. https://lnkd.in/gMFpbSuy

Can a technology called RAG keep AI models from making stuff up? Here's a quick dive into how RAG works and its potential benefits... RAG introduces an information-retrieval component to AI, enhancing its accuracy by pulling in external data. When a user queries an AI, RAG searches relevant sources, converts the query into a vector representation, and cross-checks it with external databases. This process augments the AI's response with up-to-date and accurate information, often citing sources for better reliability. Key Benefits: - Improves the accuracy of AI responses by leveraging external data. - Can update external data continuously without altering the underlying AI model. - Enhances domain-specific knowledge, making it valuable for specialized fields like medicine and history. Limitations: - While RAG mitigates the issue of AI "hallucinations," it’s not a perfect solution. - It helps direct AI to better sources but doesn't eliminate the fundamental issue of AI generating inaccurate information. #AI #Technology #Innovation #RAG #ArtificialIntelligence #DataScience #BusinessInnovation #ResearchAndDevelopment Melanie Peterson from RWS Group https://lnkd.in/epPdHB9D

Jack Clark, a co-founder of Anthropic AI and formerly the Policy Director of OpenAI, revisited OpenAI's GPT-2 impact and the lessons he learned over the years. Here are Jack Clark's main insights about AI development and deployment: In 2019, OpenAI released GPT-2, showcasing the potential of scaling laws and paving the way for models like GPT-3 and ChatGPT. Due to potential risks, OpenAI opted for a partial release, which sparked criticism as it was seen as marketing-driven and against academic norms. Predictions for GPT-2 included both beneficial uses (like AI writing assistants) and harmful ones (such as fake news and spam). Many of these predictions came true with later models. The most disruptive uses of AI have been economic, generating low-grade content driven by online incentives, rather than the feared malicious uses. According to Jack Clark, predicting AI risks and their timing is challenging. Here is what Jack thinks is important: 1) Accessibility of AI: Easy-to-use interfaces like ChatGPT have made advanced AI more accessible, boosting its benefits and risks. 2) AI policy: Balance innovation and regulation with humility and caution to avoid slowing progress. 3) Social impact: Monitoring AI's societal effects and tech progress is crucial. balanced measures adapt to changes without overreach. For more Jack Clark's insights, read the full essay reflecting on GPT-2's impact and future implications: https://lnkd.in/ewrQxSav

Here's how #AI is being ranked, according to OpenAI. Five levels, and ChatGPT is about to reach level 2: https://lnkd.in/diry6-VV

Have you heard of AI RAGs? Personally, I think AI RAGs will play a major role in the future of AI tech! “LLM users can use RAG to generate content from trusted, proprietary sources, giving them the ability to quickly and repeatedly generate text that is up-to-date and relevant," says Ellen Brandenberger, senior director of product innovation at Stack Overflow. This means that AI can produce more contextual and relevant content. It can also help reduce AI hallucinations. #AI #FutureOfAI #AIRAGs