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ai-generator17 · 1 year ago

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AI Writer & Text Generator

There are several free AI-powered text generators and caption generators available online that can help you generate captions, content, or text.

AI Writer & Text Generator, Please Click This

Here are a few options:

OpenAI's GPT-3 Demo: While not entirely free, OpenAI offers a GPT-3 demo that allows you to generate text. You may need to join a waitlist or get access through an API key. Visit the OpenAI website for more information.

ChatGPT: You are currently interacting with ChatGPT, which can assist you in generating text and captions. It's not entirely free, but you can use it within the provided limits.

CaptionBot by Microsoft: Microsoft offers CaptionBot, which can generate captions for images. It's a free online tool.

AI Dungeon: While it's primarily a text-based adventure game, AI Dungeon uses AI to generate stories and text based on your inputs. There's a free version available.

Write with Transformer by Hugging Face: Hugging Face offers a free online tool called "Write with Transformer" that lets you generate text using various models, including GPT-2. You can use it to create captions, stories, or any other text.

Copy.ai: This tool offers a limited free version and allows you to generate various types of content, including captions, marketing copy, blog posts, and more.

Snazzy AI: Snazzy AI provides a free version that allows you to create marketing content, including captions and social media posts, using AI-generated text.

Sudowrite: Sudowrite is a writing assistant that offers a free version and can help you generate text and improve your writing.

Remember that while these tools can be helpful for generating text and captions, it's essential to review and edit the content they produce to ensure it aligns with your intended message and style. Additionally, the availability and features of these tools may change over time, so it's a good idea to check their respective websites for the most up-to-date information.

Artificial Intelligence (AI) is a field of computer science that focuses on creating systems and machines that can perform tasks that typically require human intelligence. These tasks include problem-solving, learning, reasoning, perception, language understanding, and decision-making. AI systems aim to replicate or simulate human cognitive functions, and they can be used in various applications across different industries.

Here are some key aspects of AI:

Types of AI:

Narrow AI (or Weak AI): This type of AI is designed for a specific task or a narrow set of tasks. It operates under a predefined set of rules and doesn't possess general intelligence. Examples include virtual personal assistants like Siri and Alexa.

General AI (or Strong AI): General AI refers to machines that possess human-like intelligence and can perform any intellectual task that a human can. This level of AI is still largely theoretical and has not been achieved as of my last knowledge update in September 2021.

Machine Learning (ML): Machine learning is a subset of AI that focuses on developing algorithms that enable computers to learn from and make predictions or decisions based on data. Deep learning, a subfield of ML, has gained prominence for its ability to handle complex tasks such as image and speech recognition.

Natural Language Processing (NLP): NLP is a branch of AI that deals with the interaction between computers and human language. It enables machines to understand, interpret, and generate human language, making applications like chatbots and language translation possible.

Computer Vision: Computer vision involves teaching computers to interpret and understand visual information from the world, such as images and videos. It's used in facial recognition, object detection, autonomous vehicles, and more.

Robotics: AI is applied to robotics to create intelligent machines capable of performing physical tasks autonomously. This is used in industries like manufacturing, healthcare, and agriculture.

Reinforcement Learning: In reinforcement learning, AI systems learn by trial and error. They receive feedback in the form of rewards or punishments based on their actions and use this feedback to improve their decision-making processes.

Ethical and Social Considerations: AI raises various ethical and societal questions, including concerns about bias in AI algorithms, job displacement due to automation, privacy issues, and the impact of AI on society as a whole. Addressing these concerns is an ongoing challenge.

Applications of AI: AI has applications across a wide range of industries, including healthcare (diagnosis and treatment planning), finance (algorithmic trading and fraud detection), entertainment (recommendation systems), transportation (autonomous vehicles), and more.

AI Research and Development: AI research is a rapidly evolving field, with ongoing efforts to improve AI algorithms, increase their efficiency, and make AI more accessible to developers and organizations.

AI Ethics and Regulation: Governments and organizations are increasingly focusing on establishing guidelines and regulations for AI development and deployment to ensure its responsible and ethical use.

AI has the potential to bring about significant advancements in technology, automation, and problem-solving. However, it also poses challenges that need to be carefully considered to harness its benefits while mitigating risks and ethical concerns. AI will likely continue to play a prominent role in shaping the future of technology and society.

there were no truly free AI text generators available for unlimited and unrestricted use. However, there were some platforms that offered limited free access to their AI writing tools. These platforms often provided a limited number of tokens (words) or limited features in their free plans, and they might have had paid plans for more extensive use.

It's possible that the landscape has changed since then, and new platforms or tools have emerged. To find the most up-to-date information on free AI text generators, you can try searching online or checking AI-related forums and communities. Keep in mind that the availability of free AI tools can vary, and the capabilities of free versions may be limited compared to paid options.

Additionally, you can consider using open-source AI models like GPT-3.5 if you have the technical knowledge to set them up and run them. These models are freely available, but you would need to provide your own infrastructure and compute resources to use them.

Always make sure to read the terms of service and usage policies of any AI platform or tool you decide to use to ensure compliance with their policies and any applicable laws or regulations.

AI writers and text generators offer several advantages, making them valuable tools in various contexts. Here are some of the key advantages:

Efficiency: AI writers can generate content quickly and consistently, saving a significant amount of time compared to human writers. This is especially useful for tasks that require a large volume of content, such as content marketing, product descriptions, or data entry.

Cost Savings: By automating content generation, businesses can reduce labor costs associated with hiring and paying human writers. This is particularly beneficial for smaller businesses and startups with limited budgets.

Consistency: AI writers maintain a consistent tone, style, and formatting throughout their output, ensuring that the content adheres to brand guidelines and maintains a professional image.

24/7 Availability: AI writers are available round the clock, allowing organizations to generate content at any time, even outside of regular working hours.

Multilingual Support: Many AI writers can generate content in multiple languages, enabling businesses to reach a global audience more effectively.

Customization: AI writers can be fine-tuned to produce content tailored to specific niches or industries, ensuring that the generated text aligns with the target audience's interests and needs.

Reduction of Writer's Block: AI can help overcome writer's block by providing content suggestions, outlines, or even fully generated paragraphs or sentences, serving as creative prompts for human writers.

Data-Driven Insights: Some AI writers can analyze data and generate reports, summaries, or insights from raw data, simplifying complex data analysis tasks.

Scalability: AI writers can easily scale to meet the growing demands for content generation as a business expands, without the need for extensive hiring or training.

Content Variety: AI writers can create a wide range of content types, from articles and blog posts to product descriptions, social media posts, and more, providing versatility in content production.

A/B Testing: AI can assist in A/B testing by generating multiple versions of content for testing purposes, helping businesses determine what resonates best with their audience.

Content Generation for SEO: AI writers can optimize content for search engines by incorporating relevant keywords, meta descriptions, and other SEO elements, potentially improving search rankings.

AI Writer & Text Generator, Please Click This

#ai #machinelearning #technology #datascience #python

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globaljobalert-blog · 1 year ago

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Senior Product Designer - Remote, (USA, Canada Or Brazil)

Company: Chameleon Highlights - Chameleon is SaaS for product teams to create in-product UX (modals, banners, checklists, microsurveys etc.) to drive user engagement. Watch a short demo here (or sign up here) - We’re a remote-first, Series A, VC-backed (Matrix Partners, True Ventures) startup with ~45 folks distributed across the Americas and Europe. Learn more about us here. - Seeking our third Product Designer; someone with 5+ years of SaaS design experience living in US 🇺🇸, Canada 🇨🇦, or Brazil 🇧🇷 working across our products doing end-to-end design work. - Salary range is $90k - $160k USD annually, based on experience and location. - Our application process is engaging and interactive — we want to focus on your work quality, not just your interviewing skills, while getting to know you during the process. Why this role now? Our product team is ~10 engineers, 3 QAs, 1 PM (Tj), 2 designers (Valentin, Russ), and our founders (Pulkit & Brian). We are building the best product in our category and are shipping great functionality, (see this or our LinkedIn page) but we want to go even faster 🚀 We are concurrently hiring a second PM, and expect that with this we’ll be able to build two pods of work (core and growth/new) with our designers supporting work across projects and themes. We raised a Series A last year after years of bootstrapping with sustained growth, so are in a financially strong position. We have never conducted layoffs and believe in thoughtful hiring. Listen to Valentin and Russ talk about the Design team and process Video (2023-06-23 17_15 GMT+1).mp4 🔮 Where are we heading? It’s a great time to join as we have product-market fit, established the fundamentals of operating as a product team, and work with over 300 outstanding customer, such as Twilio Segment, Mixpanel, Copy.ai, Fivetran, Chili Piper, and more. View some of our case studies here! Users now expect personalized software that caters to their specific needs and context. This is hard to build and manage at scale, but the companies that succeed with this product-led approach are the winners. This provides Chameleon the opportunity to create a category-shaping product that is a part of every company’s stack! 🌐 More on our product, team, culture, and vision here. 📅 What your day might include (+ our stack) - Reviewing and contributing on our product roadmap (Notion) - Researching patterns, components, and flows from other tools (web) - Joining or conducting meetings (we use Zoom, Fathom) for research/discovery - Doing mockups, hi-fidelity designs, and creating prototypes (Figma) - Presenting in our daily design syncs with the product team (Tuple) - Async sharing of designs and or problems for feedback (Loom) - Testing and giving feedback on engineering stories (Chameleon testing accounts) - Updating our design system and component library (zeroheight) Skills and experience that will aid success in this role - 5+ years of full-time product design at a SaaS company where software is the product - 1+ years of startup ( - Experience designing complex product workflows, ideally B2B, from ideation to high-fidelity mocks, and take a system-centric approach to design (think and work with components) - Great at independent research (e.g. competitive analysis, usability testing, surveys, and interviews, etc.) specifically identifying challenges related to usability and adoption - Structured thinking, organized work, clear written and verbal communication - Proficient in Figma or similar tool - You have a fully functioning workstation and a quiet place to work (and take calls) with a high-speed internet connection - You are - Able to join functional and cross-team meetings between 8-10:30am PST - This will be your full-time job (no other part-time roles) - Fluency (written and verbal) in English - Competitive compensation ($90k - $160k USD, based on experience and location) - Early-stage equity (stock options) at a great valuation - New Macbook and $1,000 home-office budget - Flexible work hours, asynch culture and generous paid time off, plus Flexible Fridays! - Fully-paid international team retreats and mini-meetups (last one was in Miami; see - Access to True Ventures portfolio events, workshops, and networking - Ongoing coaching and mentorship from a leadership team that will help you rapidly develop and advance in your career - - - - - This job opening is available on the respective company website as of 4 - Candidates are requested to study and verify all the job details before applying and contact the respective company representative in case they have any queries. - The owner of this site has provided all the available information regarding the location of the job i.e. work from anywhere, work from home, fully remote, remote, etc. However, if you would like to have any clarification regarding the location of the job or have any further queries or doubts; please contact the respective company representative. Viewers are advised to do full requisite enquiries regarding job location before applying for each job. - Authentic companies never ask for payments for any job-related processes. Please carry out financial transactions (if any) at your own risk. - All the information and logos are taken from the respective company website. Read the full article

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techinfofacts · 2 years ago

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There are 7 free artificial intelligence tools you should know about

It’s no secret that artificial intelligence fascinates us. We consider 7 free artificial intelligence (AI)) tools, most of them easy to use and some more sophisticated… like building ML models. In this post, we are trying to be original and avoid the many AI platforms found in most Best AI Tools posts. Further, we wanted to make them free for testing, so you wouldn’t have to enter your credit card information. Many of these are products we use ourselves, so we included them imperative we value what they offer (e.g., Lumen, JADBio). Ai Technology nowadays most demand in the market

There’s not a lot on the list, but we’ll be revisiting it frequently. I consider this version to be the first.

7 free artificial intelligence tools

GFP-GAN — Photo Restoration

 Free AI tool GFP-GAN can instantly fix most old photos. By merging info from two AI models, Tencent researchers developed GFP-GAN (Generative Facial Prior-Generative Adversarial Network) to fill in missing details in photos with realistic detail in a few seconds, while maintaining high quality and accuracy. Louis Bouchard enthusiastically describes how well the free photo restoration project works in this 2-minute video. I am very impressed by the results and they work well even with very low-quality images.

A free demo of GFP-GAN is available. In addition to posting the code, the creators have provided instructions on how to use the restoration technology for any project.

Copy.ai — CopyWriter

By simply providing a brief description of every topic you want content on, this AI-based copywriting tool will produce unique content for your blog, social media, or even for a video.

Content creators may find Copy.AI useful. This tool can be used to write Instagram captions, blog posts, product descriptions, and Facebook content, as well as idea generation for start-ups.

 The AI tool generates content based on your description of the topic of interest after you sign up for an account. The future of digital content will be made easier with this awesome tool.

Website

Facebook

Twitter

Using AI to create content is not the only option available. Many are available, some are better than others, so we suggest you try them all.

JADBio — AutoML

 User-friendly and equipped with powerful knowledge extraction tools, JADBio is a machine-learning platform that does not require coding expertise. Despite being designed specifically for biotech and multi-omics, you can basically upload any kind of curated data and analyze it. It would be very useful for students who want to learn about machine learning or people who want to build a predictive model, for instance, which potato will yield the best fry (binary classification). Their lifetime free account is pretty straightforward, and they offer a lifetime free account.

DALL-E 2 — Image Creator

 It’s no secret that this one has been getting a lot of buzzes. DALL·E 2 by Open AI is an AI system that can create realistic images and artwork based on natural language descriptions. A text description can be converted into original, realistic images and art. In addition to concepts, attributes, and styles, it can also combine them. Worth playing around with, the website has several examples to inspire you. It’s completely free to use.

Notion.ai — CopyWriter

The Notion AI feature is being tested to create content. The app actually creates content good quality right in front of you, whether it’s a blog post, an email template, or a list of business books you should read. This will definitely take Notion to the next level for note-taking. Our team signed up to test it, but we are currently on the waiting list (as of Nov.16th).

Lumen5 — Video Creator

A platform called Lumen5 allows you to make videos effortlessly in a few steps. Various social media platforms are supported as well as great templates. Using your imported transcript, the AI creates the entire video sequence, including images, using your uploaded transcript. The tool is great for creating fast content for social media platforms, especially if you want to post quickly. A wide variety of images and videos can also be included in your final video with Lumen.

Lalal.ai — Audio Stem Splitter

 Artificial intelligence is used by Laval to remove vocals and separate music sources quickly, easily, and precisely. Tracks such as vocals, instrumentals, drums, bass, piano, electric guitar, acoustic guitar, and synthesizers can be removed without losing quality. Create a painless creative process! The free trial gives you 10 minutes to play around, and the paid models are very reasonable as well. 15 euros One-time payment of 15 euros for 90 minutes of processing will get you far.

Source:- https://techinfofacts.com/free-ai-tools-you-should-know-about/

#7 free artificial intelligence (AI)) tools #Artificial intelligence #Best AI Tools

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agshtgujh1 · 2 years ago

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Copy.ai Review & Demo - Is Copy AI The Best Copywriting Tool?

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mindthump · 4 years ago

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Language supermodel: How GPT-3 is quietly ushering in the A.I. revolution https://ift.tt/3mAgOO1

OpenAI

OpenAI’s GPT-2 text-generating algorithm was once considered too dangerous to release. Then it got released — and the world kept on turning.

In retrospect, the comparatively small GPT-2 language model (a puny 1.5 billion parameters) looks paltry next to its sequel, GPT-3, which boasts a massive 175 billion parameters, was trained on 45 TB of text data, and cost a reported $12 million (at least) to build.

“Our perspective, and our take back then, was to have a staged release, which was like, initially, you release the smaller model and you wait and see what happens,” Sandhini Agarwal, an A.I. policy researcher for OpenAI told Digital Trends. “If things look good, then you release the next size of model. The reason we took that approach is because this is, honestly, [not just uncharted waters for us, but it’s also] uncharted waters for the entire world.”

Jump forward to the present day, nine months after GPT-3’s release last summer, and it’s powering upward of 300 applications while generating a massive 4.5 billion words per day. Seeded with only the first few sentences of a document, it’s able to generate seemingly endless more text in the same style — even including fictitious quotes.

Is it going to destroy the world? Based on past history, almost certainly not. But it is making some game-changing applications of A.I. possible, all while posing some very profound questions along the way.

What is it good for? Absolutely everything

Recently, Francis Jervis, the founder of a startup called Augrented, used GPT-3 to help people struggling with their rent to write letters negotiating rent discounts. “I’d describe the use case here as ‘style transfer,'” Jervis told Digital Trends. “[It takes in] bullet points, which don’t even have to be in perfect English, and [outputs] two to three sentences in formal language.”

Powered by this ultra-powerful language model, Jervis’s tool allows renters to describe their situation and the reason they need a discounted settlement. “Just enter a couple of words about why you lost income, and in a few seconds you’ll get a suggested persuasive, formal paragraph to add to your letter,” the company claims.

This is just the tip of the iceberg. When Aditya Joshi, a machine learning scientist and former Amazon Web Services engineer, first came across GPT-3, he was so blown away by what he saw that he set up a website, www.gpt3examples.com, to keep track of the best ones.

“Shortly after OpenAI announced their API, developers started tweeting impressive demos of applications built using GPT-3,” he told Digital Trends. “They were astonishingly good. I built [my website] to make it easy for the community to find these examples and discover creative ways of using GPT-3 to solve problems in their own domain.”

Fully interactive synthetic personas with GPT-3 and https://t.co/ZPdnEqR0Hn ????

They know who they are, where they worked, who their boss is, and so much more. This is not your father's bot… pic.twitter.com/kt4AtgYHZL

— Tyler Lastovich (@tylerlastovich) August 18, 2020

Joshi points to several demos that really made an impact on him. One, a layout generator, renders a functional layout by generating JavaScript code from a simple text description. Want a button that says “subscribe” in the shape of a watermelon? Fancy some banner text with a series of buttons the colors of the rainbow? Just explain them in basic text, and Sharif Shameem’s layout generator will write the code for you. Another, a GPT-3 based search engine created by Paras Chopra, can turn any written query into an answer and a URL link for providing more information. Another, the inverse of Francis Jervis’ by Michael Tefula, translates legal documents into plain English. Yet another, by Raphaël Millière, writes philosophical essays. And one other, by Gwern Branwen, can generate creative fiction.

“I did not expect a single language model to perform so well on such a diverse range of tasks, from language translation and generation to text summarization and entity extraction,” Joshi said. “In one of my own experiments, I used GPT-3 to predict chemical combustion reactions, and it did so surprisingly well.”

More where that came from

The transformative uses of GPT-3 don’t end there, either. Computer scientist Tyler Lastovich has used GPT-3 to create fake people, including backstory, who can then be interacted with via text. Meanwhile, Andrew Mayne has shown that GPT-3 can be used to turn movie titles into emojis. Nick Walton, chief technology officer of Latitude, the studio behind GPT-generated text adventure game AI Dungeon recently did the same to see if it could turn longer strings of text description into emoji. And Copy.ai, a startup that builds copywriting tools with GPT-3, is tapping the model for all it’s worth, with a monthly recurring revenue of $67,000 as of March — and a recent $2.9 million funding round.

“Definitely, there was surprise and a lot of awe in terms of the creativity people have used GPT-3 for,” Sandhini Agarwal, an A.I. policy researcher for OpenAI told Digital Trends. “So many use cases are just so creative, and in domains that even I had not foreseen, it would have much knowledge about. That’s interesting to see. But that being said, GPT-3 — and this whole direction of research that OpenAI pursued — was very much with the hope that this would give us an A.I. model that was more general-purpose. The whole point of a general-purpose A.I. model is [that it would be] one model that could like do all these different A.I. tasks.”

Many of the projects highlight one of the big value-adds of GPT-3: The lack of training it requires. Machine learning has been transformative in all sorts of ways over the past couple of decades. But machine learning requires a large number of training examples to be able to output correct answers. GPT-3, on the other hand, has a “few shot ability” that allows it to be taught to do something with only a small handful of examples.

Plausible bull***t

GPT-3 is highly impressive. But it poses challenges too. Some of these relate to cost: For high-volume services like chatbots, which could benefit from GPT-3’s magic, the tool might be too pricey to use. (A single message could cost 6 cents which, while not exactly bank-breaking, certainly adds up.)

Others relate to its widespread availability, meaning that it’s likely going to be tough to build a startup exclusively around since fierce competition will likely drive down margins.

Christina Morillo/Pexels

Another is the lack of memory; its context window runs a little under 2,000 words at a time before, like Guy Pierce’s character in the movie Memento, its memory is reset. “This significantly limits the length of text it can generate, roughly to a short paragraph per request,” Lastovich said. “Practically speaking, this means that it is unable to generate long documents while still remembering what happened at the beginning.”

Perhaps the most notable challenge, however, also relates to its biggest strength: Its confabulation abilities. Confabulation is a term frequently used by doctors to describe the way in which some people with memory issues are able to fabricate information that appears initially convincing, but which doesn’t necessarily stand up to scrutiny upon closer inspection. GPT-3’s ability to confabulate is, depending upon the context, a strength and a weakness. For creative projects, it can be great, allowing it to riff on themes without concern for anything as mundane as truth. For other projects, it can be trickier.

Francis Jervis of Augrented refers to GPT-3’s ability to “generate plausible bullshit.” Nick Walton of AI Dungeon said: “GPT-3 is very good at writing creative text that seems like it could have been written by a human … One of its weaknesses, though, is that it can often write like it’s very confident — even if it has no idea what the answer to a question is.”

Back in the Chinese Room

In this regard, GPT-3 returns us to the familiar ground of John Searle’s Chinese Room. In 1980, Searle, a philosopher, published one of the best-known A.I. thought experiments, focused on the topic of “understanding.” The Chinese Room asks us to imagine a person locked in a room with a mass of writing in a language that they do not understand. All they recognize are abstract symbols. The room also contains a set of rules that show how one set of symbols corresponds with another. Given a series of questions to answer, the room’s occupant must match question symbols with answer symbols. After repeating this task many times, they become adept at performing it — even though they have no clue what either set of symbols means, merely that one corresponds to the other.

GPT-3 is a world away from the kinds of linguistic A.I. that existed at the time Searle was writing. However, the question of understanding is as thorny as ever.

“This is a very controversial domain of questioning, as I’m sure you’re aware, because there’s so many differing opinions on whether, in general, language models … would ever have [true] understanding,” said OpenAI’s Sandhini Agarwal. “If you ask me about GPT-3 right now, it performs very well sometimes, but not very well at other times. There is this randomness in a way about how meaningful the output might seem to you. Sometimes you might be wowed by the output, and sometimes the output will just be nonsensical. Given that, right now in my opinion … GPT-3 doesn’t appear to have understanding.”

An added twist on the Chinese Room experiment today is that GPT-3 is not programmed at every step by a small team of researchers. It’s a massive model that’s been trained on an enormous dataset consisting of, well, the internet. This means that it can pick up inferences and biases that might be encoded into text found online. You’ve heard the expression that you’re an average of the five people you surround yourself with? Well, GPT-3 was trained on almost unfathomable amounts of text data from multiple sources, including books, Wikipedia, and other articles. From this, it learns to predict the next word in any sequence by scouring its training data to see word combinations used before. This can have unintended consequences.

Feeding the stochastic parrots

This challenge with large language models was first highlighted in a groundbreaking paper on the subject of so-called stochastic parrots. A stochastic parrot — a term coined by the authors, who included among their ranks the former co-lead of Google’s ethical A.I. team, Timnit Gebru — refers to a large language model that “haphazardly [stitches] together sequences of linguistic forms it has observed in its vast training data, according to probabilistic information about how they combine, but without any reference to meaning.”

“Having been trained on a big portion of the internet, it’s important to acknowledge that it will carry some of its biases,” Albert Gozzi, another GPT-3 user, told Digital Trends. “I know the OpenAI team is working hard on mitigating this in a few different ways, but I’d expect this to be an issue for [some] time to come.”

OpenAI’s countermeasures to defend against bias include a toxicity filter, which filters out certain language or topics. OpenAI is also working on ways to integrate human feedback in order to be able to specify which areas not to stray into. In addition, the team controls access to the tool so that certain negative uses of the tool will not be granted access.

“One of the reasons perhaps you haven’t seen like too many of these malicious users is because we do have an intensive review process internally,” Agarwal said. “The way we work is that every time you want to use GPT-3 in a product that would actually be deployed, you have to go through a process where a team — like, a team of humans — actually reviews how you want to use it. … Then, based on making sure that it is not something malicious, you will be granted access.”

Some of this is challenging, however — not least because bias isn’t always a clear-cut case of using certain words. Jervis notes that, at times, his GPT-3 rent messages can “tend towards stereotypical gender [or] class assumptions.” Left unattended, it might assume the subject’s gender identity on a rent letter, based on their family role or job. This may not be the most grievous example of A.I. bias, but it highlights what happens when large amounts of data are ingested and then probabilistically reassembled in a language model.

“Bias and the potential for explicit returns absolutely exist and require effort from developers to avoid,” Tyler Lastovich said. “OpenAI does flag potentially toxic results, but ultimately it does add a liability customers have to think hard about before putting the model into production. A specifically difficult edge case to develop around is the model’s propensity to lie — as it has no concept of true or false information.”

Language models and the future of A.I.

Nine months after its debut, GPT-3 is certainly living up to its billing as a game changer. What once was purely potential has shown itself to be potential realized. The number of intriguing use cases for GPT-3 highlights how a text-generating A.I. is a whole lot more versatile than that description might suggest.

Not that it’s the new kid on the block these days. Earlier this year, GPT-3 was overtaken as the biggest language model. Google Brain debuted a new language model with some 1.6 trillion parameters, making it nine times the size of OpenAI’s offering. Nor is this likely to be the end of the road for language models. These are extremely powerful tools — with the potential to be transformative to society, potentially for better and for worse.

Challenges certainly exist with these technologies, and they’re ones that companies like OpenAI, independent researchers, and others, must continue to address. But taken as a whole, it’s hard to argue that language models are not turning to be one of the most interesting and important frontiers of artificial intelligence research.

Who would’ve thought text generators could be so profoundly important? Welcome to the future of artificial intelligence.

#IFTTT #Feedly #good to know #tech #hmmm #TIL #science #future

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ai-generator17 · 1 year ago

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AI Writer & Text Generator

There are several free AI-powered text generators and caption generators available online that can help you generate captions, content, or text.

For AI Writer & Text Generator, Please Click This