AI World Abuzz Over Mysteriously Released GPT2-Chatbot

Elon Musk Raising $6B for xAI

Read time: 5 minutes

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Musk chasing down big-money investors for his company xAI, while a powerful new GenAI model of unknown origin appears out of seemingly nowhere. Could it be a preview of OpenAI’s forthcoming ChatGPT-5 version?

TODAY’S AI-POWERED MARKETING UPDATE:

  • Top Story: AI World Abuzz Over Mysteriously Released GPT2-Chatbot

  • Rocket Man: Elon Musk Raising $6B for xAI

  • Tech Innovation: AI-Powered Customer Interview Tech Provider Glaut Raises $1.4M

  • AI Lawfare: OpenAI Faces ChatGPT Privacy Violation Lawsuit in EU

  • ROI Analysis: Customer Feedback the Smartest Marketing Application for GenAI

TOP STORY

AI World Abuzz Over Mysteriously Released GPT2-Chatbot

A new AI model called GPT2-Chatbot of unknown origins was released on Monday through a website that compares AI language systems and—according to some initial expert reviews—demonstrates some capabilities on par or superior to OpenAI’s popular Chat-GPT4.

“There is a mysterious new model called gpt2-chatbot accessible from a major LLM benchmarking site,” Ethan Mollick, a professor at the Wharton School of the University of Pennsylvania, posted on X. “No one knows who made it or what it is, but I have been playing with it a little and it appears to be in the same rough ability level as GPT-4.”

“Maybe better than GPT-4,” Mollick added. “Hard to tell, but it does do much better at the iconic “draw a unicorn with code”’ task.”

Some observers speculate GPT2 Chatbot might be an OpenAI creation, while others think it could have come from a less prominent development lab looking to create buzz and demonstrate its advanced chops.

ROCKET MAN

Elon Musk Raising $6B for xAI

Elon Musk’s company xAI is in the process of raising $6 billion at a pre-money valuation of $18 billion, in a deal that would sell around a quarter of the company and fund numerous AI tech initiatives.

Musk’s strategy for xAI, founded less than a year ago, involves integrating and leveraging data generated from his other companies, including X (formerly Twitter), Tesla, and Neuralink to power new AI models. It could mean qualitatively better chat and search solutions based on xAI’s Grok chatbot, a program designed to support more natural and engaging human-to-computer conversations.

“Grok can access and process information from the real world through the X platform, providing you with accurate and up-to-date answers to your questions,” according to xAI. “It even has a ‘rebellious streak’ and can tackle ‘spicy’ topics that other AI might shy away from.”

“Grok’s creative capabilities allow you to generate different forms of text content like poems, code, scripts, musical pieces, and more,” say the technology’s creators (or at least their marketing content).

According to a TechCrunch report, certain synergies between Musk’s various enterprises could emerge as each one generates and shares massive amounts of different types of data that might support as-yet unknown, new applications.

“Musk’s connection to these other companies is a feature, not a bug,” the report says. XAI could get access to crucial training data from across his empire — and its technology could, in turn, help Tesla achieve its dream of true self-driving cars and bring its humanoid Optimus robot into factories.”

AI TECH INNOVATION

AI-Powered Customer Interview Tech Provider Glaut Raises $1.4M

Glaut, an Italy-based startup that supports large-scale customer interviews which are conducted by an AI solution, has raised $1.4 million in a seed investment round.

Founded late last year, Glaut enables market researchers to execute qualitative research customer based on automated voice interviews, which are then parsed for useful data by the company’s natural language processing tech, in real time.

The service aims to replace traditional, checkbox-style market surveys and provide more in-depth insights about customer attitudes and preferences. According to Glaut, “People say 3x more with audio.”

Major brands such as Conde Nast and research agencies including Altum Insights, Eumetra, and Marketagent have already deployed Glaut’s platform to some degree, according to the company.

AI LAWFARE

OpenAI Faces ChatGPT Privacy Violation Lawsuit in EU

Noyb, an Austria-based personal privacy advocacy group, has filed a complaint against OpenAI in the EU, citing the company’s own admission that it’s “unable to correct incorrect information on ChatGPT,” and that it “cannot say where the data comes from or what data ChatGPT stores about individual people.”

“Furthermore, the company cannot say where the data comes from or what data ChatGPT stores about individual people,” noyb states. “The company is well aware of this problem, but doesn’t seem to care. Instead, OpenAI simply argues that ‘factual accuracy in large language models remains an area of active research.’”

GDPR laws in the EU require that personal information published online about individuals must be accurate and that people in turn have full access to the information stored about them—in addition to the original sources of such information.

noyb has requested that Austrian data protection authorities investigate OpenAI’s data processing and whatever measures it has or hasn’t taken to ensure accuracy of personal information processed by ChatGPT.

The advocacy group has also requested that the authority impose a fine to ensure future compliance, adding it is “likely that this case will be dealt with via EU cooperation.”

ROI ANALYSIS

Analysis: Customer Feedback the Best Marketing Application of GenAI

An article just published in Harvard Business Review, written by three accomplished authors, argues that customer-feedback analysis offers the most likely marketing application using GenAI that produces a positive ROI.

“Companies that are struggling to find the right place to deploy new AI tech should consider use cases involving ‘voice of the customer’ applications — parsing, interpreting, and responding to customer input from all different channels,” they write.

“They are typically easier to implement than employee productivity use cases because they don’t require as much behavior change, and easier to measure improvements in economic value because improving customer satisfaction often has a financial payoff.”

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