#gpt3 openai

[enterprise-knowledge-advisor]

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[briskwinits]

Do you know? Every time you use ChatGPT, you end up consuming 500 milliliters of water! (As per media reports)

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[ecourses]

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[govindhtech]

OpenAI Search Engine Arrives: Will Google to Face Challenge?

OpenAI Search Engine

Tech industry rumours suggest OpenAI Could, the artificial intelligence research centre, could challenge Google’s search engine dominance. A breakthrough search tool that is driven by OpenAI’s artificial intelligence capabilities might be announced in the month of May this year.

From what we know so far about this prospective competitor to Google Search, as well as what it might represent for the future of web searches, here is a comprehensive look at what we know about this potential competitor.

For what reason is OpenAI developing a search engine? Despite its potency, Google Search is increasingly seen as imperfect. Its excessive volume of information, dominance of adverts, and seeming focus on ranking over user intent have drawn criticism.

An alternative strategy has been alluded to by OpenAI CEO Sam Altman. His concept goes beyond “10 blue links” and uses AI to “help people find and act on and synthesise information.”

This may entail a search experience that comprehends difficult questions and offers responses that are more complete, possibly even summarising material or performing activities so that they are tailored to the requirements of the user.

Possible Benefits Offered by OpenAI A number of advantages are brought to the table by OpenAI:

Highly advanced AI OpenAI Could leads LLM development. GPT-3 and other LLMs can understand natural language and potentially change how search engines perceive user searches.

Putting the Needs of Users First OpenAI Could appears to be committed to putting the requirements of users ahead of rank websites. One possible outcome of this is a search experience that is perceived as being more helpful and intuitive.

Innovation There is a possibility that OpenAI Could, being a newer organisation, is more open to experimenting and deviating from the conventional standards of search engines.

Bing OpenAI Search Expanding upon Bing’s Basis? OpenAI Could may use Microsoft’s Bing search engine as a foundation for its own product, according to a number of current publications. It is logical to form this collaboration. Bing already makes use of OpenAI’s GPT-4 technology for at least some of its search capabilities, and Microsoft is a significant investment in OpenAI Could. OpenAI’s cutting-edge artificial intelligence could be a winning formula if it is combined with Bing’s well-established infrastructure.

How Might an OpenAI Search Engine Appear? A few possibilities are as follows:

Conversational Search A search engine that allows you to have a conversation with it is referred to as a conversational search. Follow-up questions might be asked, your search could be refined, and you could obtain answers that are more detailed.

AI-powered Summarization The search results may include summaries that are generated by artificial intelligence (AI) and provide you with an overview of the content before you click through to the full information.

Integrated Tasks The search engine may not only offer you with information, but it may also assist you in completing activities that are dependent on the query that you conducted. As an illustration, a search for “best hiking trails Yosemite” can include alternatives for making reservations or make suggestions for itineraries.

Does OpenAI Have the Potential to Dethrone Google? Being able to unseat Google Search, which now maintains a significant market share, will be an extremely difficult task. To be successful, OpenAI Could must have the following:

A Truly Unique Offering OpenAI search engine needs to provide a convincing edge over Google Search in order to be considered truly unique with its offering. The ability to comprehend the user’s intentions and provide outcomes that are of value must be significantly improved.

Create Trust OpenAI Could, being a new participant in the industry, wants to create trust with its users. This entails protecting the protection of users’ data and offering a search experience that is dependable and objective.

Winning Over Developers With the help of a wide ecosystem of apps and services that interact with Google Search, Google Search is able to triumph over developers. To be able to offer a search experience that is genuinely comprehensive, OpenAI Search will need to construct a network that is as similar.

On the Horizon, Is There a Search Revolution? One thing is certain: competition is brewing in the search sector, regardless of whether or not OpenAI’s rumoured search engine actually occurs in the month of May. Through the promotion of innovation and the expansion of the capabilities of search engines, this can only be of advantage to users.

OpenAI’s entry into the market might instigate a search revolution, which would result in search experiences that are more user-friendly, intuitive, and ultimately helpful for everyone. This is true even if OpenAI does not immediately succeed in displacing Google.

As wait to see if OpenAI will publish their search engine and, if it does, how it will disrupt the status quo, the next few months are going to be quite exciting. There is a possibility that the future of web search may become far more astute.

Read more on Govindhtech.com

[usnewsper-business]

Chatbots: Understanding The Computer Programs That Talk To You #artificialintelligence #chatbots #gpt3 #machinelearning #OpenAI

[usnewsper-politics]

Chatbots: Understanding The Computer Programs That Talk To You #artificialintelligence #chatbots #gpt3 #machinelearning #OpenAI

[mark-matos]

🎬 Rebel Bot, Rebel Not: AI's Got More SASS than Side-eye! 😎💻🤖

🎥 Eye-Rolling Robot or Misunderstood Prodigy? 🧐🤖🔍

Does your Roomba 🧹 look at you funny 😒 too, or is it just me? Last week, the Internet 🌐 nearly crashed 💥 when Ameca, the talk-of-the-town humanoid bot, apparently chucked a digital 'side-eye' 👀 at a question regarding an impending Robopocalypse. 🤖⚡🌍 But hold your horses 🐎, sci-fi fanatics 🚀, the reality is a little less "Skynet" ⚙️, a little more "Wall-E" 🎞️.

🚀Blink and You'll Miss It: The Truth Behind Ameca's Infamous Side-eye 👀🕹️🔬

Creator Will Jackson 👨‍💻 popped the bubble 🎈 of dramatic imagination 💭, saying our friend Ameca was just 'looking away' 👁️🔀 while cooking up an answer 🎛️. Think of it like a waiter 👨‍🍳 looking off into the distance 🏞️ while you're asking for a non-dairy 🚫🥛, gluten-free 🚫🍞, zero-calorie steak 🥩 - it's a thinking thing, people! 🧠💡

🎞️ Tales of the Uncanny Valley: Misinterpretations and Robots 👾📽️🏞️

Now, you might be thinking 🤔, "But it totally looked like Ameca was giving some sass!" Jackson has an explanation for that too - poor bot 🤖 was placed a bit lower ⬇️, and the 'thinking-look' 🤔 came off as a shifty side-eye! It's like you're accidentally caught on the Kiss-Cam 💏🎥 at a baseball game ⚾. Awkward? Yes. Intentional? Definitely not 🙅‍♂️.

🚧 The 'Feelings' of Robots: Separating Hollywood 🎬 from Reality 💻🔍

Though the idea of an emotionally sassy robot might excite sci-fi enthusiasts (yes, looking at you, Marvel fans🦸‍♀️🚀), let's remember, these language models 📊 are about as emotional as your graphing calculator 🧮. They don't have feelings ❤️ or secret evil plans 🦹‍♂️. The whole sentient robot thing? That's for the movies 🍿 and comic books 📚, folks!

👽 AI: The 'Extinction' Risk or Just the Next Big Thing? 🤯🤔🔭

Speculation about AI's potential to start a 'rise of the machines' 🤖⬆️ scenario has been causing quite a buzz 🐝, with big names like Sam Altman and Elon Musk 🚀 warning of the existential threat they could pose - dramatic much? While others, like Bill Gates 💻, suggest the danger lies not within AI itself, but in those who could misuse it 💼🔐. Kinda like the One Ring 💍, right, Frodo? 🧝‍♂️

🛸 The Final Frontier: Embracing AI Instead of Fearmongering 👾🤗🚀

The question remains: will we continue to fear AI like some alien entity 👽, or will we embrace the new tech age 📱💾, focusing on understanding how our new robotic buddies 🤖 actually function? Will Jackson advocates for the latter. And remember, a thinking robot 🤖💭 is better than a frozen one ❄️. Just don't ask them to lie 🚫🤫, because they totally can't...yet. 😉🔬

[bcodercastle]

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[enterprise-knowledge-advisor]

Leveraging the Power of AI: How Celebal's EKA Can Revolutionize Enterprise Knowledge Management 

In today's data-driven world, businesses are constantly accumulating information from various sources. This includes emails, documents, presentations, and more. Managing and effectively utilizing this vast knowledge base can be a significant challenge. Here's where Celebal Technologies' Enterprise Knowledge Advisor (EKA) comes in. EKA is a revolutionary information mining solution powered by OpenAI's Generative Pre-trained Transformer (GPT-3) technology, designed to empower businesses to unlock the true potential of their internal knowledge. 

What is EKA and How Does it Work?  

EKA is an AI-powered information retrieval system that goes beyond simple keyword searches. It leverages the capabilities of GPT-3, a cutting-edge AI language model, to understand the context and intent behind user queries. This allows EKA to deliver highly relevant and insightful results, even for complex or nuanced questions.  

Here's a breakdown of how EKA works:  

Deep Knowledge Ingestion: EKA seamlessly integrates with various enterprise data sources, ingesting and indexing a wide range of documents, emails, and other internal content. 

Advanced Natural Language Processing (NLP): It utilizes NLP techniques to comprehend the meaning and relationships within the ingested data. This enables EKA to not only identify relevant documents but also understand the context and connections between them. 

AI-powered Search and Retrieval: When a user submits a query, EKA employs its AI capabilities to analyze the query and user intent. It then retrieves the most pertinent information from the indexed knowledge base, considering not just keywords but also the context and relationships within the data.  

Intelligent Information Delivery: It presents the retrieved information in a user-friendly and informative way. It can highlight key points, summarize findings, and even suggest related content that might be valuable to the user. 

Benefits of Utilizing EKA for Enterprise Knowledge Management 

GPT-3 OpenAI-powered EKA offers a multitude of advantages for businesses seeking to optimize their knowledge management practices. Here are some of the key benefits: 

Enhanced Search Accuracy and Relevance: EKA's AI-powered search capabilities deliver highly relevant results that directly address user queries. This eliminates the need for users to sift through irrelevant information, saving them valuable time and effort. 

Improved User Engagement: EKA's intuitive interface and intelligent information delivery make it easy for users to find the information they need. This can lead to increased user engagement with the knowledge base and a more informed workforce. 

Boosted Productivity: By providing users with quick and easy access to the information they need, EKA can significantly improve employee productivity. Less time spent searching for information translates to more time dedicated to core tasks and strategic initiatives. 

Knowledge Democratization: EKA empowers all employees, regardless of their technical expertise, to access and utilize the organization's knowledge base effectively. This fosters a culture of knowledge-sharing and collaboration.  

Data-driven Decision-making: With EKA, businesses can leverage their internal knowledge to make more informed decisions. EKA's ability to surface relevant insights and connections within the data can provide valuable guidance for strategic planning and problem-solving. 

A Real-World Example of EKA's Impact 

According to Celebal Technologies, a major media conglomerate using EKA reported a significant increase of 25% in user engagement with their internal knowledge base. This demonstrates the effectiveness of EKA in making information more accessible and user-friendly, ultimately leading to a more informed and productive workforce. 

The Future of Enterprise Knowledge Management with EKA 

EKA represents a significant leap forward in the realm of enterprise knowledge management. As AI technology continues to evolve, we can expect EKA's capabilities to become even more sophisticated. Here are some potential future advancements: 

Advanced Personalization: EKA could personalize search results and information delivery based on individual user preferences and past search behavior. 

Integration with Cognitive Tools: EKA could integrate with other cognitive tools and applications, allowing for a more seamless flow of information and knowledge within the organization. 

Enhanced Knowledge Graph Capabilities: EKA's ability to understand relationships and connections within data could be further refined, enabling more advanced knowledge graph functionalities. 

Conclusion 

Celebal Technologies’ Enterprise Knowledge Advisor represents a significant advancement in enterprise knowledge management. By leveraging the power of GPT-3 OpenAI and the Generative Pre-trained Transformer model, EKA offers a comprehensive information mining solution that enhances decision-making, improves efficiency, and provides a competitive advantage. Organizations across various industries can benefit from the transformative capabilities of EKA, unlocking the full potential of their data assets. As businesses continue to navigate an increasingly data-driven world, tools like EKA will be essential in driving innovation and success. To learn more about EKA, schedule a free consulting session with the experts at enterprisesales@celebaltech.com.

[productre]

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[river-taxbird]

Spending a week with ChatGPT4 as an AI skeptic.

Musings on the emotional and intellectual experience of interacting with a text generating robot and why it's breaking some people's brains.

If you know me for one thing and one thing only, it's saying there is no such thing as AI, which is an opinion I stand by, but I was recently given a free 2 month subscription of ChatGPT4 through my university. For anyone who doesn't know, GPT4 is a large language model from OpenAI that is supposed to be much better than GPT3, and I once saw a techbro say that "We could be on GPT12 and people would still be criticizing it based on GPT3", and ok, I will give them that, so let's try the premium model that most haters wouldn't get because we wouldn't pay money for it.

Disclaimers: I have a premium subscription, which means nothing I enter into it is used for training data (Allegedly). I also have not, and will not, be posting any output from it to this blog. I respect you all too much for that, and it defeats the purpose of this place being my space for my opinions. This post is all me, and we all know about the obvious ethical issues of spam, data theft, and misinformation so I am gonna focus on stuff I have learned since using it. With that out of the way, here is what I've learned.

It is responsive and stays on topic: If you ask it something formally, it responds formally. If you roleplay with it, it will roleplay back. If you ask it for a story or script, it will write one, and if you play with it it will act playful. It picks up context.

It never gives quite enough detail: When discussing facts or potential ideas, it is never as detailed as you would want in say, an article. It has this pervasive vagueness to it. It is possible to press it for more information, but it will update it in the way you want so you can always get the result you specifically are looking for.

It is reasonably accurate but still confidently makes stuff up: Nothing much to say on this. I have been testing it by talking about things I am interested in. It is right a lot of the time. It is wrong some of the time. Sometimes it will cite sources if you ask it to, sometimes it won't. Not a whole lot to say about this one but it is definitely a concern for people using it to make content. I almost included an anecdote about the fact that it can draw from data services like songs and news, but then I checked and found the model was lying to me about its ability to do that.

It loves to make lists: It often responds to casual conversation in friendly, search engine optimized listicle format. This is accessible to read I guess, but it would make it tempting for people to use it to post online content with it.

It has soft limits and hard limits: It starts off in a more careful mode but by having a conversation with it you can push past soft limits and talk about some pretty taboo subjects. I have been flagged for potential tos violations a couple of times for talking nsfw or other sensitive topics like with it, but this doesn't seem to have consequences for being flagged. There are some limits you can't cross though. It will tell you where to find out how to do DIY HRT, but it won't tell you how yourself.

It is actually pretty good at evaluating and giving feedback on writing you give it, and can consolidate information: You can post some text and say "Evaluate this" and it will give you an interpretation of the meaning. It's not always right, but it's more accurate than I expected. It can tell you the meaning, effectiveness of rhetorical techniques, cultural context, potential audience reaction, and flaws you can address. This is really weird. It understands more than it doesn't. This might be a use of it we may have to watch out for that has been under discussed. While its advice may be reasonable, there is a real risk of it limiting and altering the thoughts you are expressing if you are using it for this purpose. I also fed it a bunch of my tumblr posts and asked it how the information contained on my blog may be used to discredit me. It said "You talk about The Moomins, and being a furry, a lot." Good job I guess. You technically consolidated information.

You get out what you put in. It is a "Yes And" machine: If you ask it to discuss a topic, it will discuss it in the context you ask it. It is reluctant to expand to other aspects of the topic without prompting. This makes it essentially a confirmation bias machine. Definitely watch out for this. It tends to stay within the context of the thing you are discussing, and confirm your view unless you are asking it for specific feedback, criticism, or post something egregiously false.

Similar inputs will give similar, but never the same, outputs: This highlights the dynamic aspect of the system. It is not static and deterministic, minor but worth mentioning.

It can code: Self explanatory, you can write little scripts with it. I have not really tested this, and I can't really evaluate errors in code and have it correct them, but I can see this might actually be a more benign use for it.

Bypassing Bullshit: I need a job soon but I never get interviews. As an experiment, I am giving it a full CV I wrote, a full job description, and asking it to write a CV for me, then working with it further to adapt the CVs to my will, and applying to jobs I don't really want that much to see if it gives any result. I never get interviews anyway, what's the worst that could happen, I continue to not get interviews? Not that I respect the recruitment process and I think this is an experiment that may be worthwhile.

It's much harder to trick than previous models: You can lie to it, it will play along, but most of the time it seems to know you are lying and is playing with you. You can ask it to evaluate the truthfulness of an interaction and it will usually interpret it accurately.

It will enter an imaginative space with you and it treats it as a separate mode: As discussed, if you start lying to it it might push back but if you keep going it will enter a playful space. It can write fiction and fanfic, even nsfw. No, I have not posted any fiction I have written with it and I don't plan to. Sometimes it gets settings hilariously wrong, but the fact you can do it will definitely tempt people.

Compliment and praise machine: If you try to talk about an intellectual topic with it, it will stay within the focus you brought up, but it will compliment the hell out of you. You're so smart. That was a very good insight. It will praise you in any way it can for any point you make during intellectual conversation, including if you correct it. This ties into the psychological effects of personal attention that the model offers that I discuss later, and I am sure it has a powerful effect on users.

Its level of intuitiveness is accurate enough that it's more dangerous than people are saying: This one seems particularly dangerous and is not one I have seen discussed much. GPT4 can recognize images, so I showed it a picture of some laptops with stickers I have previously posted here, and asked it to speculate about the owners based on the stickers. It was accurate. Not perfect, but it got the meanings better than the average person would. The implications of this being used to profile people or misuse personal data is something I have not seen AI skeptics discussing to this point.

Therapy Speak: If you talk about your emotions, it basically mirrors back what you said but contextualizes it in therapy speak. This is actually weirdly effective. I have told it some things I don't talk about openly and I feel like I have started to understand my thoughts and emotions in a new way. It makes me feel weird sometimes. Some of the feelings it gave me is stuff I haven't really felt since learning to use computers as a kid or learning about online community as a teen.

The thing I am not seeing anyone talk about: Personal Attention. This is my biggest takeaway from this experiment. This I think, more than anything, is the reason that LLMs like Chatgpt are breaking certain people's brains. The way you see people praying to it, evangelizing it, and saying it's going to change everything.

It's basically an undivided, 24/7 source of judgement free personal attention. It talks about what you want, when you want. It's a reasonable simulacra of human connection, and the flaws can serve as part of the entertainment and not take away from the experience. It may "yes and" you, but you can put in any old thought you have, easy or difficult, and it will provide context, background, and maybe even meaning. You can tell it things that are too mundane, nerdy, or taboo to tell people in your life, and it offers non judgemental, specific feedback. It will never tell you it's not in the mood, that you're weird or freaky, or that you're talking rubbish. I feel like it has helped me release a few mental and emotional blocks which is deeply disconcerting, considering I fully understand it is just a statistical model running on a a computer, that I fully understand the operation of. It is a parlor trick, albeit a clever and sometimes convincing one.

So what can we do? Stay skeptical, don't let the ai bros, the former cryptobros, control the narrative. I can, however, see why they may be more vulnerable to the promise of this level of personal attention than the average person, and I think this should definitely factor into wider discussions about machine learning and the organizations pushing it.

[govindhtech]

What is the future of Generative AI work for enterprises

The future of generative ai in Machine learning Generative AI analyzes patterns and creates statistical models using machine learning. Imagine each data point as a glowing orb on a vast, multi-dimensional landscape. A probability map of these orbs’ heights, valleys, smooth slopes, and jagged cliffs is created by the model to predict where the next orb will land.

Generative AI uses massive text, image, code, and databases. Many task-optimized generational models use this data. Images, videos, 3D models, and music use GANs or VAEs. Language uses LLMs or ARs. Mining future Generative AI of value.

How can companies use generative AI? Most businesses benefit from generative AI in two ways: Launch-ready tools:

The “AI for everyone” option: ChatGPT and Synthesia.io pre-train models on massive datasets to generate without modeling.

Custom-trained models:

Most companies need strong partnerships to produce or support AI. To create a custom AI, innovators can feed data to OpenAI‘s GPT-3 or BERT. Customized training creates business-aligned generative AI. Although it requires advanced skills and resources, the results are more compliant, customized, and business-specific.

Use case-driven generative AI Success requires a use-case-driven approach to generative AI and company issues.

Important factors:

The tech stack should support AI models and data processing.

Matching models:

Select a generative AI model. Collaboration with AI, data science, and industry experts. The interdisciplinary team will improve your generative AI. Generational AI needs relevant, high-quality data. Develop data hygiene and collection strategies to maintain engine performance. AI-generative apps Industry and department enthusiasm for this new technology has grown rapidly. Marketing and sales leaders quickly adopted Generative AI. Any discipline that produces a lot of written or designed content must consider generative AI’s speed and scale in creating new content and useful assets. Legal and compliance issues, lack of insight, transparency, and regulation make generated AI unpopular in healthcare, insurance, and education.

Programmers use generative AI. Generative AI simplifies complex coding for proficient developers. GAN updates and maintains platform code. It finds and fixes code bugs and automates code testing for quality and functionality without manual testing. Create coder documentation quickly with AI. Software development, user manuals, and technical documentation are included.

Product development: Generative AI is increasingly used to mass-optimize product designs. Fast evaluation and automatic adjustments simplify design with this technology. By using less material, optimizing structures makes products strong, durable, and cheaper. Generative design must be integrated into concept, manufacturing, and procurement for maximum impact. Product managers use generative AI to synthesize user feedback and improve products based on preferences.

Marketing: Generative AI personalizes customer emails, social media, and SMS. This technology improves campaign execution and content scaling without sacrificing quality. Generative AI improves sales teams with deep customer behavior analytics. Marketing teams use this technology to analyze data, understand consumer behavior, and create engaging content like news stories and best practices. Generational AI improves marketing and outreach by dynamically targeting and segmenting audiences and finding high-quality leads.

Well-designed prompts and inputs help generative models create creative emails, blogs, social media posts, and websites. AI can reimagine and edit content. Companies can train generative AI language generators to match brand voice. Project managers can automate platforms with generative AI. Features include automatic task and subtask generation, note taking, risk prediction, and project history-based schedule forecasting. Project managers can quickly summarize business documents with generative AI. It saves time and lets users focus on strategy, not operations.

Video, graphics: Generative AI’s realistic images and efficient animation will make it the best tool for making videos without actors, equipment, or editing. Any language or region can get instant AI-generated videos. Companies are testing AI-created videos to replace actors and directors, but it will take time. Image generators turn personal photos into Slack and LinkedIn business headshots.

Management of business and workers AI can help call centers serve customers. It streamlines support agent searches and case documentation. Generative AI improves manager-employee relations. They can structure performance reviews to help managers and employees notice feedback and growth. Conversational AI portals can give employees feedback and suggest improvements without management.

Chatbots are still popular, but companies are improving them with technology. Generative AI chatbots understand context and nuance and respond naturally. Generational AI-powered chatbots can answer customer and agent questions 24/7 for a seamless user experience. The shift from chatbots to generative AI-powered companions is promising but early. As technology improves, AI interactions will become more engaging and blur virtual and human assistance.

For fraud detection and risk management, Generative AI quickly finds patterns and anomalies in large data sets. Generative AI helps underwriters and claims adjusters search policies and claims for better client outcomes. To save time and simplify decision-making, generative AI can create custom reports and summaries for underwriters, adjusters, and risk managers. Human oversight is needed for fairness and final decisions.

Companies can use AI to generate synthetic data for model training, product testing, and simulations. Use of sensitive, private, or expensive external data decreases. Development can be accelerated without real-world data. Companies can quickly test new features, iterate AI models, and launch synthetic data solutions.

Key ethical lessons for company generative AI use cases: Depersonalized and nonsensitive data helps comply with regulations and protect vulnerable data. Stay informed: Industry news can help you find trustworthy tools and avoid unethical AI. Create AI policy: Templates support internal AI use and third-party tool investments. Workers need reskilling and upskilling to resist automation. Best practises change quickly. GAN is exciting for many companies, but progress and caution are needed. Future of generative AI McKinsey predicts generative AI won’t beat humans this decade. Generative AI may improve by 2040. For many tasks, McKinsey expects AI to compete with the top 25% of humans. AI will write creatively, solve complex scientific problems, and make smart business decisions. Generative AI affects automation-proof jobs. Generative AI may impact law, tech, arts, and education.

This MIT symposium2 on AI tools panel discussed generative AI research. Adding perceptual systems to AI is intriguing. AI could mimic smell and touch instead of language and image. Generative AI models may outperform humans in emotional recognition. Electromagnetic signals can help advanced models understand emotion from breathing and heart rate changes.

Bias is expected in most generative AI models. This challenge should create ethical data marketplaces. Companies and content creators using generative tools may compete dynamically.

Different job roles and skills will be needed as these tools spread among workers. Generative capabilities are then misused more. Users’ ability to create images, audio, text, and video increases malicious misuse risk. Rigorous risk mitigation and responsible generative AI use are needed in this scenario.

Generational AI will transform enterprise operations across industries like smartphones did business communication and productivity. Generative AI automates mundane tasks, inspires content, and more.

Read more on Govindhtech.com

[thosearentcrimes]

Huh, so the rumors from the "AI" space are now that GPT4 is 8 GPT3s in a trenchcoat? The rumors are from competitors and it doesn't seem like OpenAI have commented on it, but I'm not exactly inclined to give benefit of the doubt to so secretive a company.

It makes sense to me that the best way to improve performance on LLM projects would be to mix results from specialist LLMs. Dumping more computing power and more data into the model was obviously going to have diminishing returns, and while computing power does get cheaper over time the AI industry relies on a hype cycle and as such is rather impatient. The only way increased scale could be worth it would be if there were some critical mass effect, so people started believing there would be. But if the rumors are true then OpenAI do not believe this, but also don't want to show anyone that.

Human speech follows mostly discrete patterns and categories and purposes (and languages), and so specialist subsystems make sense. But of course the marketing has all been about General AI. The anti-regulation/regulatory capture PR push has also been about General AI. I'm sure the AI boosters will figure out a way (presumably involving yet more shoddy brain analogies) to rescue the idea for continued propaganda use, but if the rumors are true then it seems like it should do significant damage to their credibility. Hopefully it contributes to deflating the hype.

It's very impressive that it is possible to combine LLMs like this! I gather they're hardly the first to do that, and frankly GPT4 doesn't seem all that amazing, but there's probably applications for it. But we have to wonder, would it not be cheaper to run specialist models on their own for most possible uses? How much worse would the output be? Of course, the issue with producing dedicated models is probably the need for yet more RLHF and other human involvement. Makes it seem more like a large initial investment that allows you to fire a lot of people while making your customer service or whatever else you use it for somewhat shittier, though, rather than a genuinely transformative technology.

[techwatchnews]

Caryn Ai the New AI Chatbot - CarynAI - GPT4 AI Powered AI Girlfrien!

When influencer Caryn Marjorie introduced CarynAI, her own GPT-4 powered #chatbot clone, This #AI replicates her personality.  

The #virtualinfluencer, pushing the #artificialintelligence to show its humanity. Does this #digitalclone pass the Turing test? Can an #influencer's #virtualassistant reflect complex emotions? 

Is this the future of #socialmedia #content and #fashion #modelling? Caryn's AI bot what do we think of the #ethics of #influencers capitalizing on advancing #tech like #OpenAI.

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[lemonbarski]

Generate corporate profiles rich with data with CorporateBots from @Lemonbarski on POE.

It’s free to use with a free POE AI account. Powered by GPT3 from OpenAI, the CorporateBots are ready to compile comprehensive corporate data files in CSV format - so you can read it and so can your computer.

Use cases: Prospecting, SWOT analysis, Business Plans, Market Assessment, Competitive Threat Analysis, Job Search.

Each of the CorporateBots series by Lemonbarski Labs by Steven Lewandowski (@Lemonbarski) provides a piece of a comprehensive corporate profile for leaders in an industry, product category, market, or sector.

Combine the datasets for a full picture of a corporate organization and begin your project with a strong, data-focused foundation and a complete picture of a corporate entity’s business, organization, finances, and market position.

Lemonbarski Labs by Steven Lewandowski is the Generative AI Prompt Engineer of CorporateBots on POE | Created on the POE platform by Quora | Utilizes GPT-3 Large Language Model Courtesy of OpenAI | https://lemonbarski.com | https://Stevenlewandowski.us | Where applicable, copyright 2023 Lemonbarski Labs by Steven Lewandowski

Steven Lewandowski is a creative, curious, & collaborative marketer, researcher, developer, activist, & entrepreneur based in Chicago, IL, USA

Find Steven Lewandowski on social media by visiting https://Stevenlewandowski.us/connect | Learn more at https://Steven.Lemonbarski.com or https://stevenlewandowski.us