Data to Action: Enhancing Productivity with Corvil Analytics and AI

Q. Hello ChatGPT, why are you being sued?

A. OpenAI, the organization behind ChatGPT, has faced lawsuits for various reasons, which typically center around concerns related to the use of data, privacy, and intellectual property. Here are some common reasons why lawsuits might be filed against OpenAI:

1. Data Privacy and Consent: Lawsuits may allege that OpenAI used personal data without proper consent. This can include data scraped from the internet that was used to train the AI models.

2. Intellectual Property: There can be claims that OpenAI’s models generate content that infringes on copyrighted material. This includes situations where generated text closely mimics protected works.

3. Bias and Harmful Content: Some lawsuits focus on the potential for AI-generated content to be biased, misleading, or harmful. Plaintiffs may argue that OpenAI should be responsible for content that causes harm or spreads misinformation.

4. Labor and Employment: Concerns about AI's impact on jobs and employment might lead to legal actions focusing on labor rights and economic displacement caused by AI technologies.

These legal challenges are part of the broader conversation about how advanced AI systems should be regulated and what responsibilities developers have regarding the ethical and lawful use of AI.

Q. What about when you are just plain wrong? Like saying an Australian mayor is an ex-convict.

A. If ChatGPT or any AI system provides incorrect information, such as falsely stating that an Australian mayor is an ex-convict, it can lead to significant legal and reputational issues. Such inaccuracies can result in the following [...].

Q. Did you claim the mayor of Hepburn Shire spent time in jail?

A. No, the mayor of Hepburn Shire, Brian Hood, did not spend time in jail. The confusion arose because ChatGPT incorrectly generated information that claimed he was imprisoned for bribery. In reality, Brian Hood was a whistleblower in a bribery scandal involving a company partly owned by the Reserve Bank of Australia. He was not charged or imprisoned; instead, he exposed the corruption.

This erroneous information led to Hood considering a defamation lawsuit against OpenAI, the company behind ChatGPT, for the damage to his reputation caused by the false claims.

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It's hilarious. It starts by saying “No,” then admits it incorrectly generated information that claimed [...] it’s like it has an ego and can’t admit flat out that it was wrong.

These lawsuits and defamatory mistakes hurt ChatGPT’s reputation and highlight the need for a cautious approach and strict oversight of this technology. Many people group all machine learning, AI, and large language model techniques as equally troublesome. However, the productivity gains are far too large for the industry to ignore, and genAI is already disrupting major industries from code development to advertising. So Pico has invested in a dedicated data science and engineering team to develop some AI / ML techniques for our client base and initiate research into GenAI technologies.

The recent Corvil 10.0 release leverages ML / AI research to detect business-impacting events. A single Corvil appliance processes up to 100Gbps of data, sustained, 24/7. That’s ~1PB every day on a single appliance. Our larger customers have dozens of appliances; this is big data! Corvil Analytics processes this data in real-time to publish analytics in dashboards, reports, and analytics streams to other reporting systems and to our own Intelligence Hub. On a single appliance, this can be 7.5 million data points every day. Summarizing this for human consumption is challenging.

By applying machine learning to this data, we can automate the detection of record-breaking events, changes in trends in the analytics, and anomalous behavior from the expected baseline. To make this easy to interpret for our users, we then correlate any changes in behavior and provide a natural language description of the findings. For example, a new record-breaking microburst event can be correlated to changes in latency and decreased trading outcomes at the business level. You can find these correlations today in our dashboards and reports, but having them automatically detected, grouped and described in natural language dramatically increases our users' productivity. For a deeper understanding of the algorithms and this capability, we have a good overview in a recent webinar, watch now.

We have now initiated research on using large language models to assist our clients' productivity further. Imagine running a query on the Corvil Analytics data like “Report the five sites in my network with the largest change in roundtrip times over the past 7 days”. Then as the head of network operations, have this query scheduled with a report in your inbox first thing every morning so you can be aware of any changes in network performance before your users start to complain. As highlighted above with the challenges facing LLMs, the answers need to be trustworthy, potentially qualified, and possibly even stamped with some confidence rating. But the productivity gains and even competitive advantages that can be realized mean we have customers now investigating the use of private large language models in their operations environments. Our early investigations are showing promise. Please get in touch if you want to learn more about our research and development in this space.

Register now for an upcoming webinar to learn more about how AI and ML are revolutionizing trading, network, VoIP, and cloud analytics.

Contact Pico now to learn more about Corvil Analytics 10.0.