The world raved about AI last year, even Jensen Huang from Nvidia famously praised the power of Artificial Intelligence (AI). He went as far as to say anyone can be a programmer with AI softwares. This was during the period where ChatGPT got into trouble in various shapes and forms— from data security breach to fabricated content by a high ranking editor.

Now, the chip titan finds itself joining the group of defendants accused of copyright infringements via OpenAI. Three authors reportedly took Nvidia to court over using their copyrighted material without permission to train its NeMo AI platform.

Brian Keene, Abdi Nazemian and Stewart O’Nan said their works were part of a dataset of about 196,640 books that helped train NeMo to simulate ordinary written language, before being taken down in October “due to reported copyright infringement.“ In a proposed class action filed in San Francisco federal court, the authors said the takedown reflects Nvidia’s having “admitted” it trained NeMo on the dataset, and thereby infringed their copyrights.

They are seeking unspecified damages for people in the United States whose copyrighted works helped train NeMo’s so-called large language models in the last three years. Among the works covered by the lawsuit are Keene’s 2008 novel “Ghost Walk,” Nazemian’s 2019 novel “Like a Love Story,” and O’Nan’s 2007 novella “Last Night at the Lobster.”

The lawsuit drags Nvidia into a growing body of litigation by writers, as well as the New York Times, over generative AI, which creates new content based on inputs such as text, images and sounds. Nvidia touts NeMo as a fast and affordable way to adopt generative AI.

Other companies sued over the technology have included OpenAI, which created the AI platform ChatGPT, and its partner Microsoft. AI’s rise has made Nvidia a favourite of investors. The Santa Clara, California-based chipmaker’s stock price has risen almost 600% since the end of 2022, giving Nvidia a market value of nearly US$2.2 trillion.

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Axios reported engineers and programmers across many industries have found great utility in refining code or double-checking their work by running it through ChatGPT. However, there has not been a lot of transparency around the collection of that data, where it goes or how it could potentially be used.

Using ChatGPT in corporate settings is about to get a lot easier after Salesforce unveiled plans this week to integrate the large language model chatbot into Slack. Salesforce isn’t alone. Several technology companies, including Snap, have been racing to integrate generative AI into their consumer-facing products and tools.

Increasingly, employers are getting nervous about how employees might use ChatGPT at work. Walmart and Amazon have both reportedly warned employees not to share confidential information in the chatbot.

An Amazon corporate lawyer told employees the company has already seen instances of ChatGPT responses that are similar to internal Amazon data, according to Insider. JPMorgan Chase & Co. and Verizon have reportedly blocked employee access to the online tool.

Meanwhile, OpenAI changed its terms of service so its models no longer use user inputs by default to train amid growing concerns about privacy risks. 2.3% of workers have put confidential company information into ChatGPT, according to a recent report from Cyberhaven. Samsung’s is the latest to be in the hot seat when one of their core divisions had confidential coding data retained by the chatbot (unknowingly).

Another Camp For It

In another side of the world, there is a camp that found the chatbot to be performing better than humans in predicting stock performances! A recent study conducted by researchers at the University of Florida shows that ChatGPT, a large language model, can accurately forecast stock market returns using sentiment analysis of news headlines. However, it failed to acknowledge the chatbot’s pool of data cuts off at September 2021.

Business Today reported The study, titled “Return Predictability and Large Language Models,” found that ChatGPT outperformed traditional sentiment analysis methods provided by leading vendors. The researchers leveraged ChatGPT’s sentiment analysis capabilities to analyse news headlines and predict whether they were good, bad, or irrelevant news for firms’ stock prices.

They then computed a numerical score and documented a positive correlation between these “ChatGPT scores” and subsequent daily stock market returns. The research has significant implications for the finance industry. According to the paper, this finding has the potential to shift the methods used for market prediction and investment decision-making.

Doubts In Confidence

However, no further details were revealed on the mechanics of the chatbot’s predictions. After Samsung’s recent fiasco with ChatGPT regarding its semiconductors, the biggest revelation was the chatbot was actively mining data from sources (discreetly)? The fact that its reliability is under scrutiny is incriminating for the financial sector to be supremely cautious about predicting stock performances.

Applying the cut off date to the chatbot where it is quick to dish a disclaimer on the limitations of information availability, it is plausible predictions were based on standard mathematical methodologies and theories. Martingale is the mathematical method of predicting the future price of a stock based on the stock’s current price. According to this theory, past returns or results do not matter in present scenarios and predict future prices. This concept is part of probability theory. Hence, what it projects could potentially be based on outdated data.

Applying this to metalworking; for CNC, programmers are responsible for the proper operation and programming of CNC machines using CNC programming that allows sending instructions to motorised tools. CNC programming plays a crucial role in ensuring efficient and accurate machine operation.

The most common programming language used to run CNC machines is G-code (also known as G programming). With G-code, a programmer can control various movements and functions of a CNC tool

Where does it leave the machine tool sector where programming is instrumental in ensuring efficiency and accuracy? If engineers accessed ChatGPT for improving coding, they are not protected from having their data mined and disseminated.

Samsung is planning to develop their own ChatGPT for cybersecurity. When such drastic actions are in the pipeline, industries should exercise caution — using the tool for consultation purposes without compromising the organisation’s integrity.

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The post Companies Struggle To Protect Corporate Secrets From ChatGPT appeared first on Asia Pacific Metalworking Equipment News | Manufacturing | Automation | Quality Control.