Information Analytics

According to a new global study conducted by S&P Global Market Intelligence and commissioned by WEKA, the adoption of artificial intelligence (AI) by enterprises and research organizations seeking to create new value propositions is accelerating, but data infrastructure and AI sustainability challenges present barriers to implementing it successfully at scale. These challenges have been exacerbated by the rapid onset of generative AI that has defined the evolution of the AI market in 2023.

At this point, ChatGPT has firmly established itself into the cultural zeitgeist. People are using it to perform tasks like writing research papers, completing math equations, and crafting code. It is at least a part (if not a frontrunner) of a recent wave of AI generators that can make whatever your heart desires when you input phrases and parameters into the prompt box provided by the app. But all of that may be put on pause as a research paper out of Stanford University and UC Berkeley is claiming that ChatGPT is degrading in accuracy.

OpenText has announced opentext.ai, described as a new strategic approach to advance how its customers can solve complex problems by applying Artificial Intelligence (AI) and Large Language Models (LLM) with their OpenText Information Management software.

Mindbreeze has added the ability to leverage innovations in Generative AI for sensitive enterprise data securely within its Knowledge Management solutions. Advanced Large Language Models (LLM) combined with Mindbreeze InSpire provide natural language processing, text generation, and data security.

New Zealand digitisation and workflow systems provider Desktop Imaging has announced a partnership with US digital intelligence company ABBYY.

It strikes me as paradoxical that businesses feel very secure in using artificial intelligence to let people know, for example, when it is safe to make a lane change at 100 kilometres per hour, yet they are reticent to use the same technology to classify and manage information through its lifecycle. Artificial Intelligence is used almost every minute of every day, in nearly every smart device we own. 

Generative AI tools such as Midjourney, Stable Diffusion and DALL-E 2 have astounded us with their ability to produce remarkable images in a matter of seconds. Despite their achievements, however, there remains a puzzling disparity between what AI image generators can produce and what we can. For instance, these tools often won’t deliver satisfactory results for seemingly simple tasks such as counting objects and producing accurate text.

There’s been much ado about the pros and cons of artificial intelligence over the last few months since the start of the ChatGPT era. Generative AI has hit the mainstream; new vendor solutions are cropping up daily and professionals from many different industries are giving it a test drive.

Australian firm Katonic.ai is looking to capitalise on the surge in interest in Generative AI, offering a range of different options to integrate the technology with corporate applications. The company has delivered a portal that provides an opportunity to test a large number of open source large language models (LLMs), with more than 50 to choose from at https://playground.katonic.ai/

Ground Labs has announced the general availability of Enterprise Recon 2.9.0. The latest version of this sensitive data discovery solution delivers improved data risk scoring capabilities along with security and functionality enhancements in addition to offering new personal data types and maintenance updates.

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