The Verge

NOVEMBER 2, 2021

GPT-3 is the best known example of a new generation of AI language models. These limited applications make sense given the huge problems associated with large AI language models like GPT-3. Second: these models have also been shown time and time again to incorporate biases found in their training data, from sexism to Islamaphobia.

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TechCrunch

AUGUST 8, 2023

The recent terms & conditions controversy sequence goes like this: A clause added to Zoom’s legalese back in March 2023 grabbed attention on Monday after a post on Hacker News claimed it allowed the company to use customer data to train AI models “with no opt out” Cue outrage on social media.

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Candid

AUGUST 10, 2023

Before we get completely swept up, let’s not forget the previous technology hype cycles that have come and gone. 2) Fast follow The Gartner Hype Cycle captures the euphoria new technologies tend to generate in the early days. has likely put it near the peak of the hype cycle.

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TechCrunch

APRIL 4, 2023

The hype around ChatGPT , OpenAI’s viral AI-powered chatbot, hasn’t reached a peak yet. ” That new ventures are jumping on the ChatGPT hype train isn’t surprising, considering ChatGPT’s virality. .” ” and get the answer in natural language.

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DataRobot

SEPTEMBER 21, 2021

AI Hype Versus Narrow AI. You can train an AI to do one narrowly defined task under certain controlled circumstances. For example, state-of-the-art language models are increasing in size by at least a factor of ten every year. Cost limitations: The cost of training and running AI models increases with their complexity and size.

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The Verge

MAY 20, 2020

The typical stage and hype were removed, and it felt like dialing into a Microsoft Teams call that moved from one house to the next. That’s reflected in a variety of languages supported in closed captions in the Build streams and even American Sign Language support. We didn’t just pull Build out of our butts.”.

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InfoWorld

APRIL 8, 2024

We need to have a frank conversation about large language models (LLMs). The hype surrounding LLMs has reached stratospheric levels, fostering a misguided belief in their potential as AGI precursors. The clamor for LLMs to evolve into AGI solutions epitomizes tunnel vision at its finest.

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Towards Data Science

OCTOBER 7, 2023

The hype around generative AI is real, and data and ML teams are feeling the heat. And tech giants like OpenAI, Google, Amazon, and Microsoft have been flooding the market with features driven by large language models (LLMs) and image-generating diffusion models. Getting started with LLMs? Image courtesy of author.

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TechCrunch

FEBRUARY 16, 2023

Natural language processing ( NLP ), while hardly a new discipline, has catapulted into the public consciousness these past few months thanks in large part to the generative AI hype train that is ChatGPT. million ($2.9 These include Argilla, which recently raised a $1.6

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TechCrunch

AUGUST 3, 2022

” The way Sudhakar explains it, Aisera’s platform learns to resolve issues through a combination of language-analyzing AI and robotic process automation, or RPA. The platform supposedly recognizes over 70 languages, but does it understand all of those languages equally well? upselling). Image Credits: Aisera.

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TechCrunch

APRIL 19, 2023

For many, ChatGPT and the generative AI hype train signals the arrival of artificial intelligence into the mainstream. According to Gartner, unstructured data constitutes as much as 90% of new data generated in the enterprise, and is growing three times faster than the structured equivalent. .

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Fast Company Tech

FEBRUARY 12, 2025

She points to a paper from OpenAI the same company that partnered with Apple for news summarizationwhich concluded that well-calibrated language models must hallucinate as part of their creative process. “We’ve seen the hype cycles around massively open online courses that were going to transform education,” Waltzer says.

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InfoWorld

APRIL 4, 2024

Once you get past the chatbot hype, it’s clear that generative AI is a useful tool, providing a way of navigating applications and services using natural language. By tying our large language models (LLMs) to specific data sources, we can avoid the risks that come with using nothing but training data.

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The Verge

MAY 26, 2021

As this tech is adopted, users will be able to “talk to Google”: using natural language to retrieve information from the web or their personal archives of messages, calendar appointments, photos, and more. The richness and flexibility of language make it one of humanity’s greatest tools and one of computer sciences’ greatest challenges”.

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Non Profit Quarterly

FEBRUARY 17, 2025

They dont reflect all of society, because the training data that are used to produce these mirror images are like the light falling on a mirror. Butand heres the first qualification these AI tools that are built to generate reflections of human intelligence dont reflect all of us. And a mirror can only reflect the light that reaches it.

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TechCrunch

MAY 13, 2023

The venture capitalist was one of many at an AI confab last month, but he — and many others — has not yet made a new AI investment during the current hype cycle. Here’s an excerpt: Precursor’s Charles Hudson wants to be cautious but not too cautious. I don’t think I’m OK with zero as the answer for AI. The question is where and how.”

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TechCrunch

NOVEMBER 26, 2021

Email is what Flowrite’s AI models have been trained on, per Isosaari. ” The AI tool could also be a great help to people who find writing difficult for specific reasons such as dyslexia or because English is not their native language, he further suggests. Okay, the GPT-3 hype seems pretty reasonable.

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TechCrunch

APRIL 21, 2021

Most of the language learning in the system right now is based around English and several other popular global languages such as Spanish and French. MIT professor wants to overhaul ‘The Hype Machine’ that powers social media.

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TechNode

JULY 9, 2024

Credit: Internet Why it matters: Kuaishou will be hoping that its suite of self-developed large model series, including language model KwaiYii, image-focused Kolors, and video-centered Kling, will give it an edge as it continues to challenge to ByteDance’s Douyin and TikTok.

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Tableau

MARCH 21, 2022

We’re seeing AI projects shift from hype to impact, largely because the right roles are getting involved to provide the business context that has been missing previously. A shared language of data within the organization also opens more doors for successful collaboration with experts. March 21, 2022 - 3:15pm. March 22, 2022.

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Tableau

MARCH 21, 2022

We’re seeing AI projects shift from hype to impact, largely because the right roles are getting involved to provide the business context that has been missing previously. A shared language of data within the organization also opens more doors for successful collaboration with experts. March 21, 2022 - 3:15pm. March 22, 2022.

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Towards Data Science

AUGUST 10, 2023

Still, generating a recipe for lasagna is an entirely different process than infusing generative AI capabilities across a business or integrating large language models (LLMs) into data engineering workflows. The ability for non-technical users to enter natural language prompts that can generate SQL queries to retrieve specific data points.

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TechCrunch

AUGUST 24, 2023

High profile examples of such systems, such as OpenAI’s large language model ChatGPT, have relied (at least in part) upon data posted online for training their systems — and a class action lawsuit filed against the U.S. And be used to pump out unwanted direct marketing or spam.

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TechCrunch

MARCH 3, 2023

. “We process not only famous open source projects, but also ‘pet’ projects, tests, forks and even training projects from Coursera or Udemy that engineers keep public on GitHub,” Grineva added. ” Under the hood, Prog.ai ” Under the hood, Prog.ai profile example. Image Credits: Prog.ai search example.

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TechCrunch

OCTOBER 14, 2021

However, this general policy can never account for all possible scenarios a bureaucracy will need to handle — much like an AI model cannot be trained to anticipate every possible input. If you limit the degree to which you hype up what your AI can do, you can both avoid irresponsible consequences and sell your product more effectively.

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Qgiv

MARCH 27, 2023

So what’s all the hype about? The GPT of ChatGPT stands for generative pre-trained transformer, which is a group of language models trained to generate human-like text developed by OpenAI. In fact, the AI gained over one million users in just five days after it launched!

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Towards Data Science

DECEMBER 24, 2023

So, use the the right language for your task. SQL is the least verbose “language” out of all supported spark languages for many operations! 8 — Use ChatGPT This is not about hype. Anything you send to a closed source model can become training data for the parent organization — make sure you don’t send anything sensitive.

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TechCrunch

MARCH 20, 2023

The ability to generate fresh content via algorithms has been thrust into the public consciousness by the likes of ChatGPT , a chatbot-style technology trained on large language models (LLMs) capable of producing essays, poems, lyrics, news articles, and even computer programs.

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TechCrunch

NOVEMBER 1, 2022

This might involve gathering and viewing all direct and indirect feedback in a single interface, or using one of Crowd.dev’s premium tools such as Eagle Eye , which leans on natural language processing (NLP) to identify community discussions ripe for engagement. Eagle Eye app. I mage Credits: Crowd.dev. million ($2.2

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CauseVox

MAY 11, 2023

Functionality : It’s a natural language processing (NLP) platform that comes with an easy-to-use interface and drag-and-drop functionality. A Different Kind of Chatbot: ChatGPT Lately, there’s been a lot of hype around ChatGPT. At its core, NLP is a computer program’s ability to understand spoken and written language.

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The Verge

JULY 30, 2020

GPT stands for “generative pre-training.”) To simplify things, the program has been trained on a huge corpus of text that it’s mined for statistical regularities. percent of GPT-3’s training data. The dataset GPT-3 was trained on is similarly mammoth. percent of its training data. Look at the entire video.

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Forum One

FEBRUARY 22, 2010

Some over-hype it as "magical" and "transformative." It's a great way to create better understanding across language and cultural barriers. It's a great way to create better understanding across language and cultural barriers. Apple's new iPad tablet computer has spawned some mixed reactions.

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Bloomerang

OCTOBER 29, 2021

And there are a lot of different reasons that you should focus on this, not the least of which is because you work really hard to recruit people to fundraise for you in these events, and you probably spend a lot of time training and onboarding these groups of people. So you can kind of get them hyped up about your next event.

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Fast Company Tech

MARCH 18, 2025

As the team kept winning, W+K kept hyping the connectionacross social media and IRL by turning the Empire State Building purple, and sending Grimace on the 7 train ahead of a playoff game. For longtime client Nike, W+K effectively tapped into the incredible waves of hype surrounding Caitlin Clarks final season of NCAA basketball.

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Futurism

MARCH 22, 2025

That's had a big effect on our economy, as the tiniest bit of AI hype can send huge shockwaves through Wall Street and beyond. The large language models (LLMs) that underpin products like OpenAI's ChatGPT, for instance, need to devour enormous datasets of written words to fine tune an algorithm to follow the rules of language.

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Futurism

FEBRUARY 22, 2025

The team lined seven of the top large language models (LLMs) up against Stockfish, an infamously strong chess engine that's been stumping grandmasters since 2014. So far, big tech has poured untold billions into AI training, moving fast and breaking the old internet in what some critics are calling a " race to the bottom."

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Mashable Tech

FEBRUARY 27, 2025

On Thursday, the ChatGPT maker announced the latest version of its LLM (large language model) in research preview. Persistent rumors indicate that OpenAI has seen diminishing returns in model improvements, suggesting scaling laws (more compute, bigger datasets) for training a model might not equate to improved results. OpenAI's GPT-4.5

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