What happens when genAI meets low code?
GenAI is all the rage today, but not long ago, low-code and no-code development had a moment. If developers combine these technologies, can they make programming more efficient?
When the programming language Cobol was invented in 1959, the US Department of Defense was trying to make code simpler. The Common Business-Oriented Language, like its immediate predecessor Flow-Matic, used English language prose to make the code more accessible for everyday users.
Nearly 70 years later, every subsequent advancement in code has sought the same end: Make code simpler.
In an industry full of hype cycles, generative AI, large language models (LLMs), and copilots are currently in
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@waterstechnology.com or view our subscription options here: http://subscriptions.waterstechnology.com/subscribe
You are currently unable to print this content. Please contact info@waterstechnology.com to find out more.
You are currently unable to copy this content. Please contact info@waterstechnology.com to find out more.
Copyright Infopro Digital Limited. All rights reserved.
As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.
If you would like to purchase additional rights please email info@waterstechnology.com
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@waterstechnology.com
More on Emerging Technologies
BlackRock tests ‘quantum cognition’ AI for high-yield bond picks
The proof of concept uses the Qognitive machine learning model to find liquid substitutes for hard-to-trade securities.
JP Morgan, Eurex push for DLT-driven collateral management
The high-stakes project could be a litmus test for the use of blockchain technology in the capital markets.
For AI’s magic hammer, every problem becomes a nail
A survey by Risk.net finds that banks are embracing a twin-track approach to AI in the front office: productivity tools today; transformation tomorrow.
On GenAI, Citi moves from firm-wide ban to internal roll-out
The bank adopted three specific inward-facing use cases with a unified framework behind them.
How a Chinese AI firm shook the tech world
DeepSeek’s AI model is the very ethos of doing what you can with what you have.
To unlock $40T private markets, Hamilton Lane embraced automation
In search of greater transparency and higher quality data, asset managers are taking a tech-first approach to resource gathering in an area that has major data problems.
Waters Wavelength Ep. 304: Nice Actimize’s Lee Garf
Lee joins to discuss changes in communication platforms over the last few years.
DTCC revamps data distribution, collection efforts with cloud, AI
The US clearinghouse is evaluating the possibilities that cloud and AI offer to streamline the processes by which it collects and makes data available to market participants.
