#generative pre-trained transformer | Explore Tumblr Posts and Blogs

Visit Blog

Explore Tumblr blogs with no restrictions, modern design and the best experience.

Fun Fact

China blocked Tumblr because of pornography and censorship problems in 2013.

#generative pre-trained transformer

afutureworththinkingabout · 9 months

Text

My New Article at WIRED

So, you may have heard about the whole zoom “AI” Terms of Service clause public relations debacle, going on this past week, in which Zoom decided that it wasn’t going to let users opt out of them feeding our faces and conversations into their LLMs. In 10.1, Zoom defines “Customer Content” as whatever data users provide or generate (“Customer Input”) and whatever else Zoom generates from our uses of Zoom. Then 10.4 says what they’ll use “Customer Content” for, including “…machine learning, artificial intelligence.”

And then on cue they dropped an “oh god oh fuck oh shit we fucked up” blog where they pinky promised not to do the thing they left actually-legally-binding ToS language saying they could do.

Like, Section 10.4 of the ToS now contains the line “Notwithstanding the above, Zoom will not use audio, video or chat Customer Content to train our artificial intelligence models without your consent,” but it again it still seems a) that the “customer” in question is the Enterprise not the User, and 2) that “consent” means “clicking yes and using Zoom.” So it’s Still Not Good.

Well anyway, I wrote about all of this for WIRED, including what zoom might need to do to gain back customer and user trust, and what other tech creators and corporations need to understand about where people are, right now.

And frankly the fact that I have a byline in WIRED is kind of blowing my mind, in and of itself, but anyway…

Also, today, Zoom backtracked Hard. And while i appreciate that, it really feels like decided to Zoom take their ball and go home rather than offer meaningful consent and user control options. That’s… not exactly better, and doesn’t tell me what if anything they’ve learned from the experience. If you want to see what I think they should’ve done, then, well… Check the article.

Until Next Time.

Read the rest of My New Article at WIRED at A Future Worth Thinking About

#ai #artificial intelligence #ethics #generative pre-trained transformer #gpt #large language models #philosophy of technology #public policy #science technology and society #technological ethics #technology #zoom #privacy

123 notes · View notes

dieterziegler159 · 2 months

Text

Join the conversation on the future of communication! Learn how large language models are driving innovation and connectivity.

#Large Language Models #Impact of Large Language Models #AI Language Capabilities #Contextual Understanding #Deep Learning Algorithms #Generative Pre-trained Transformer

0 notes

public-cloud-computing · 2 months

Text

From conversation to innovation, delve into the limitless possibilities of large language models. Revolutionize communication and beyond!

#Large Language Models #Impact of Large Language Models #AI Language Capabilities #Contextual Understanding #Deep Learning Algorithms #Generative Pre-trained Transformer

0 notes

enterprise-cloud-services · 2 months

Text

From conversation to innovation, delve into the limitless possibilities of large language models. Revolutionize communication and beyond!

#Large Language Models #Impact of Large Language Models #AI Language Capabilities #Contextual Understanding #Deep Learning Algorithms #Generative Pre-trained Transformer

0 notes

rubylogan15 · 2 months

Text

From conversation to innovation, delve into the limitless possibilities of large language models. Revolutionize communication and beyond!

#Large Language Models #Impact of Large Language Models #AI Language Capabilities #Contextual Understanding #Deep Learning Algorithms #Generative Pre-trained Transformer

0 notes

richdadpoor · 8 months

Text

Google Search AI Gives Ridiculous, Wrong Answers

Google’s experiments with AI-generated search results produce some troubling answers, Gizmodo has learned, including justifications for slavery and genocide and the positive effects of banning books. In one instance, Google gave cooking tips for Amanita ocreata, a poisonous mushroom known as the “angel of death.” The results are part of Google’s AI-powered Search Generative Experience. Google’s…

View On WordPress

#Alphabet Inc.#Amanita #artificial intelligence #Bing #chatgpt #Generative pre-trained transformer #Gizmodo #Google #Google Search #Internet #Internet search engines #Large language models #Lily Ray #Microsoft #Microsoft Bing #Mushroom poisoning #OPENAI #Social Issues #Technology

0 notes

drcpanda12 · 1 year

Photo

New Post has been published on https://www.knewtoday.net/the-rise-of-openai-advancing-artificial-intelligence-for-the-benefit-of-humanity/

The Rise of OpenAI: Advancing Artificial Intelligence for the Benefit of Humanity

OpenAI is a research organization that is focused on advancing artificial intelligence in a safe and beneficial manner. It was founded in 2015 by a group of technology luminaries, including Elon Musk, Sam Altman, Greg Brockman, and others, with the goal of creating AI that benefits humanity as a whole.

OpenAI conducts research in a wide range of areas related to AI, including natural language processing, computer vision, robotics, and more. It also develops cutting-edge AI technologies and tools, such as the GPT series of language models, which have been used in a variety of applications, from generating realistic text to aiding in scientific research.

In addition to its research and development work, OpenAI is also committed to promoting transparency and safety in AI. It has published numerous papers on AI ethics and governance and has advocated for responsible AI development practices within the industry and among policymakers.

Introduction to OpenAI: A Brief History and Overview

An American artificial intelligence (AI) research facility called OpenAI is made as a non-profit organization. OpenAI Limited Partnership is its for-profit sister company. The stated goal of OpenAI’s AI research is to advance and create a benevolent AI. Microsoft’s Azure supercomputing platform powers OpenAI systems.

Ilya Sutskever, Greg Brockman, Trevor Blackwell, Vicki Cheung, Andrej Karpathy, Durk Kingma, John Schulman, Pamela Vagata, and Wojciech Zaremba created OpenAI in 2015; the inaugural board of directors included Sam Altman and Elon Musk. Microsoft invested $1 billion in OpenAI LP in 2019 and another $10 billion in 2023.

Brockman compiled a list of the “top researchers in the field” after meeting Yoshua Bengio, one of the “founding fathers” of the deep learning movement. In December 2015, Brockman was able to bring on nine of them as his first workers. In 2016, OpenAI paid business compensation rather than nonprofit payments to its AI researchers, but not salaries that were on par with Facebook or Google.

Several researchers joined the company because of OpenAI’s potential and mission; one Google employee claimed he was willing to leave the company “partly because of the very strong group of people and, to a very big extent, because of its mission.” Brockman said that advancing humankind’s ability to create actual AI in a secure manner was “the best thing I could imagine doing.” Wojciech Zaremba, a co-founder of OpenAI, claimed that he rejected “borderline ridiculous” offers of two to three times his market value in order to join OpenAI.

A public beta of “OpenAI Gym,” a platform for reinforcement learning research, was made available by OpenAI in April 2016. “Universe,” a software platform for assessing and honing an AI’s general intelligence throughout the universe of games, websites, and other applications, was made available by OpenAI in December 2016.

OpenAI’s Research Areas: Natural Language Processing, Computer Vision, Robotics, and More

In 2021, OpenAI will concentrate its research on reinforcement learning (RL).

Gym

Gym, which was introduced in 2016, intends to offer a general-intelligence benchmark that is simple to deploy across a wide range of environments—similar to, but more extensive than, the ImageNet Large Scale Visual Recognition Challenge used in supervised learning research. In order to make published research more easily replicable, it aims to standardize how environments are characterized in publications on AI. The project asserts that it offers a user-friendly interface. The gym may only be used with Python as of June 2017. The Gym documentation site was no longer maintained as of September 2017, and its GitHub page was the site of ongoing activity.

RoboSumo

In the 2017 virtual reality game RoboSumo, humanoid meta-learning robot agents compete against one another with the aim of learning how to move and shoving the rival agent out of the arena. When an agent is taken out of this virtual environment and placed in a different virtual environment with strong gusts, the agent braces to stay upright, indicating it has learned how to balance in a generic fashion through this adversarial learning process. Igor Mordatch of OpenAI contends that agent competition can lead to an intelligence “arms race,” which can improve an agent’s capacity to perform, even outside of the confines of the competition.

Video game bots

In the competitive five-on-five video game Dota 2, a squad of five OpenAI-curated bots known as OpenAI Five is utilized. These bots are trained to compete against human players at a high level solely by trial-and-error techniques. The first public demonstration took place at The International 2017, the yearly premier championship event for the game, where Dendi, a professional Ukrainian player, lost to a bot in a real-time one-on-one matchup before becoming a team of five. Greg Brockman, CTO, revealed after the game that the bot had learned by competing against itself for two weeks in real-time, and that the learning software was a step toward developing software that could perform intricate jobs like a surgeon.

By June 2018, the bots had improved to the point where they could play as a full team of five, defeating teams of amateur and semi-professional players. OpenAI Five competed in two exhibition games at The International 2018 against top players, but they both lost. In a live demonstration game in San Francisco in April 2019, OpenAI Five upset OG, the current global champions of the game, 2:0.During that month, the bots made their last public appearance, winning 99.4% of the 42,729 games they participated in over a four-day open internet competition.

Dactyl

In 2018 Dactyl uses machine learning to teach a Shadow Hand, a robotic hand that resembles a human hand, how to manipulate actual objects. It uses the same RL algorithms and training code as OpenAI Five to learn totally in simulation. Domain randomization, a simulation method that exposes the learner to a variety of experiences rather than attempting to match them to reality, was used by OpenAI to address the object orientation problem. Dactyl’s setup includes RGB cameras in addition to motion tracking cameras so that the robot may control any object simply by looking at it. In 2018, OpenAI demonstrated that the program could control a cube and an octagonal prism.

2019 saw OpenAI present Dactyl’s ability to solve a Rubik’s Cube. 60% of the time, the robot was successful in resolving the puzzle. It is more difficult to model the complex physics introduced by items like Rubik’s Cube. This was resolved by OpenAI by increasing Dactyl’s resistance to disturbances; they did this by using a simulation method known as Automated Domain Randomization (ADR),

OpenAI’s GPT model

Alec Radford and his colleagues wrote the initial study on generative pre-training of a transformer-based language model, which was released as a preprint on OpenAI’s website on June 11, 2018. It demonstrated how pre-training on a heterogeneous corpus with lengthy stretches of continuous text allows a generative model of language to gain world knowledge and understand long-range dependencies.

A language model for unsupervised transformers, Generative Pre-trained Transformer 2 (or “GPT-2”) is the replacement for OpenAI’s first GPT model. The public initially only saw a few number of demonstrative copies of GPT-2 when it was first disclosed in February 2019. GPT-2’s complete release was delayed due to worries about potential abuse, including uses for creating fake news. Some analysts questioned whether GPT-2 posed a serious threat.

It was trained on the WebText corpus, which consists of little more than 8 million documents totaling 40 gigabytes of text from Links published in Reddit contributions that have received at least three upvotes. Adopting byte pair encoding eliminates some problems that can arise when encoding vocabulary with word tokens. This makes it possible to express any string of characters by encoding both single characters and tokens with multiple characters.

GPT-3

Benchmark results for GPT-3 were significantly better than for GPT-2. OpenAI issued a warning that such language model scaling up might be nearing or running into the basic capabilities limitations of predictive language models.

Many thousand petaflop/s-days of computing were needed for pre-training GPT-3 as opposed to tens of petaflop/s-days for the complete GPT-2 model. Similar to its predecessor, GPT-3’s fully trained model wasn’t immediately made available to the public due to the possibility of abuse, but OpenAI intended to do so following a two-month free private beta that started in June 2020. Access would then be made possible through a paid cloud API.

GPT-4

The release of the text- or image-accepting Generative Pre-trained Transformer 4 (GPT-4) was announced by OpenAI on March 14, 2023. In comparison to the preceding version, GPT-3.5, which scored in the bottom 10% of test takers,

OpenAI said that the revised technology passed a simulated law school bar exam with a score in the top 10% of test takers. GPT-4 is also capable of writing code in all of the major programming languages and reading, analyzing, or producing up to 25,000 words of text.

DALL-E and CLIP images

DALL-E, a Transformer prototype that was unveiled in 2021, generates visuals from textual descriptions. CLIP, which was also made public in 2021, produces a description for an image.

DALL-E interprets natural language inputs (such as an astronaut riding on a horse)) and produces comparable visuals using a 12-billion-parameter version of GPT-3. It can produce pictures of both actual and unreal items.

ChatGPT and ChatGPT Plus

An artificial intelligence product called ChatGPT, which was introduced in November 2022 and is based on GPT-3, has a conversational interface that enables users to ask queries in everyday language. The system then provides an answer in a matter of seconds. Five days after its debut, ChatGPT had one million members.

ChatGPT Plus is a $20/month subscription service that enables users early access to new features, faster response times, and access to ChatGPT during peak hours.

Ethics and Safety in AI: OpenAI’s Commitment to Responsible AI Development

As artificial intelligence (AI) continues to advance and become more integrated into our daily lives, concerns around its ethics and safety have become increasingly urgent. OpenAI, a research organization focused on advancing AI in a safe and beneficial manner, has made a commitment to responsible AI development that prioritizes transparency, accountability, and ethical considerations.

One of the ways that OpenAI has demonstrated its commitment to ethical AI development is through the publication of numerous papers on AI ethics and governance. These papers explore a range of topics, from the potential impact of AI on society to the ethical implications of developing powerful AI systems. By engaging in these discussions and contributing to the broader AI ethics community, OpenAI is helping to shape the conversation around responsible AI development.

Another way that OpenAI is promoting responsible AI development is through its focus on transparency. The organization has made a point of sharing its research findings, tools, and technologies with the wider AI community, making it easier for researchers and developers to build on OpenAI’s work and improve the overall quality of AI development.

In addition to promoting transparency, OpenAI is also committed to safety in AI. The organization recognizes the potential risks associated with developing powerful AI systems and has taken steps to mitigate these risks. For example, OpenAI has developed a framework for measuring AI safety, which includes factors like robustness, alignment, and transparency. By considering these factors throughout the development process, OpenAI is working to create AI systems that are both powerful and safe.

OpenAI has also taken steps to ensure that its own development practices are ethical and responsible. The organization has established an Ethics and Governance board, made up of external experts in AI ethics and policy, to provide guidance on OpenAI’s research and development activities. This board helps to ensure that OpenAI’s work is aligned with its broader ethical and societal goals.

Overall, OpenAI’s commitment to responsible AI development is an important step forward in the development of AI that benefits humanity as a whole. By prioritizing ethics and safety, and by engaging in open and transparent research practices, OpenAI is helping to shape the future of AI in a positive and responsible way.

Conclusion: OpenAI’s Role in Shaping the Future of AI

OpenAI’s commitment to advancing AI in a safe and beneficial manner is helping to shape the future of AI. The organization’s focus on ethical considerations, transparency, and safety in AI development is setting a positive example for the broader AI community.

OpenAI’s research and development work is also contributing to the development of cutting-edge AI technologies and tools. The GPT series of language models, developed by OpenAI, have been used in a variety of applications, from generating realistic text to aiding in scientific research. These advancements have the potential to revolutionize the way we work, communicate, and learn.

In addition, OpenAI’s collaborations with industry leaders and their impact on real-world applications demonstrate the potential of AI to make a positive difference in society. By developing AI systems that are safe, ethical, and transparent, OpenAI is helping to ensure that the benefits of AI are shared by all.

As AI continues to evolve and become more integrated into our daily lives, the importance of responsible AI development cannot be overstated. OpenAI’s commitment to ethical considerations, transparency, and safety is an important step forward in creating AI that benefits humanity as a whole. By continuing to lead the way in responsible AI development, OpenAI is helping to shape the future of AI in a positive and meaningful way.

Best Text to Speech AI Voices

#Artificial intelligence #ChatGPT #ChatGPT Plus #Computer Vision #DALL-E #Elon Musk #Future of AI #Generative Pre-trained Transformer #GPT #Natural Language Processing #OpenAI #OpenAI&039;s GPT model #Robotics #Sam Altman #Video game bots

1 note · View note

sitenesia · 10 months

Text

Bagaimana ChatGPT Bekerja? Apa SihChat-GPT: Sistem Generasi Teks Berbasis AI dari OpenAI itu?

Bagaimana ChatGPT Bekerja? Apa Sih Chat-GPT: Sistem Generasi Teks Berbasis AI dari OpenAI itu? Seperti Apa Arsitektur dan Kelebihannya? Dalam era digital yang semakin maju ini, teknologi kecerdasan buatan (Artificial Intelligence/AI) telah menjadi bagian penting dalam kehidupan sehari-hari. Salah satu perkembangan terbaru dalam bidang AI adalah ChatGPT, yang telah menarik perhatian banyak…

View On WordPress

#Apa Itu #Arsitektur #Artificial Intelligence #Asisten Virtual #Cara Kerja #Chatbot #ChatGPT #Decoder #Deep Learning #Definisi #Encoder #Generative Pre-trained Transformer #Kelebihan #Neural Network #OpenAI #Penerjemah Teks #Pengertian #Tanya Jawab Rifqi #Transformer

1 note · View note

chandrashaker · 1 year

Text

GPT-4 - The Powerhouse of Conversational AI

GPT-4 is an artificial intelligence model developed by OpenAI. It is based on the Generative Pre-trained Transformer 3.5 architecture. It is the latest iteration of the ChatGPT series. #GPT-4 #chatgpt4 #chatgpt #chatgpt3 #openai #ai #gpt

As technology continues to evolve, we are witnessing a new era of human-computer interaction, where machines are becoming more intelligent and interactive. One such example is the GPT-4, a cutting-edge conversational AI model that has revolutionized how we interact with machines. In this blog post, we will explore the capabilities of GPT-4 and how it is transforming the world of conversational…

View On WordPress

#AI #Artificial Intelligence #Chat GPT #Chat GPT-3 #Chat GPT-4 #Chatbot #ChatGPT #ChatGPT-3 #ChatGPT-4 #ChatGPT3 #ChatGPT4 #Conversational AI #Generative Pre-Trained Transformer #GPT #GPT-4 #Open AI #OpenAI

0 notes

uplymedia · 5 months

Text

Boost Your Business Edge with GPTs

A Deep Dive into the World of Customized GPTs FeatureStandard GPTsCustom GPTsKnowledge BaseBroad and generalSpecialized and focusedRelevanceGeneral-purposeHighly contextualApplicationsWide-rangingIndustry-specificCustom GPT Types Hello, dear reader! Today, We are thrilled to guide you through the fascinating world of Custom Generative Pre-trained Transformers, commonly known as Custom GPTs.…

View On WordPress

#AI Customization #AI Technology #Custom GPTs #Generative Pre-trained Transformers

0 notes

afutureworththinkingabout · 10 months

Text

My New Article at American Scientist

As of this week, I have a new article in the July-August 2023 Special Issue of American Scientist Magazine. It’s called “Bias Optimizers,” and it’s all about the problems and potential remedies of and for GPT-type tools and other “A.I.”

This article picks up and expands on thoughts started in “The ‘P’ Stands for Pre-Trained” and in a few threads on the socials, as well as touching on some of my comments quoted here, about the use of chatbots and “A.I.” in medicine.

I’m particularly proud of the two intro grafs:

Recently, I learned that men can sometimes be nurses and secretaries, but women can never be doctors or presidents. I also learned that Black people are more likely to owe money than to have it owed to them. And I learned that if you need disability assistance, you’ll get more of it if you live in a facility than if you receive care at home.

At least, that is what I would believe if I accepted the sexist, racist, and misleading ableist pronouncements from today’s new artificial intelligence systems. It has been less than a year since OpenAI released ChatGPT, and mere months since its GPT-4 update and Google’s release of a competing AI chatbot, Bard. The creators of these systems promise they will make our lives easier, removing drudge work such as writing emails, filling out forms, and even writing code. But the bias programmed into these systems threatens to spread more prejudice into the world. AI-facilitated biases can affect who gets hired for what jobs, who gets believed as an expert in their field, and who is more likely to be targeted and prosecuted by police.

As you probably well know, I’ve been thinking about the ethical, epistemological, and social implications of GPT-type tools and “A.I.” in general for quite a while now, and I’m so grateful to the team at American Scientist for the opportunity to discuss all of those things with such a broad and frankly crucial audience.

I hope you enjoy it.

Read My New Article at American Scientist at A Future Worth Thinking About