The Future of AI
torch v0.11.0 is now on CRAN! This blog post highlights some of the changes included in this release. But you can always find the full changelog on the torch website. Improved loading of state dicts For a long time it has been possible to use torch from R to load state dicts (i.e. model weights) … Read more
“Let’s just ensure that going forward, all the invoices are forwarded to Mr. X for validation before processing.” If only invoice validation were that simple. In reality, it requires systematic checks and balances, not just one person’s oversight. Studies show that 25% of invoice errors slip through accounts payable processes undetected despite internal correction efforts. … Read more
We’re planning a live virtual event later this year, and we want to hear from you. Are you using a powerful AI technology that seems like everyone ought to be using? Here’s your opportunity to show the world! AI is too often seen as an enterprise of, by, and for the wealthy. We’re going to take … Read more
When it comes to running your AR process on NetSuite, one of the most common tasks you’ll do is creating sales orders. Manually creating sales orders can be tedious – the NetSuite UI is not very straightforward, and there are further complexities that are present only in the API and not on the NetSuite UI … Read more
AI Observability in Practice Many organizations start off with good intentions, building promising AI solutions, but these initial applications often end up disconnected and unobservable. For instance, a predictive maintenance system and a GenAI docsbot might operate in different areas, leading to sprawl. AI Observability refers to the ability to monitor and understand the functionality … Read more
As the tech world buzzes with the unveiling of Apple Intelligence, expectations are soaring. The leap from iPhone to AI-Phone paints a picture of a future where our devices aren’t just tools but partners capable of anticipating our needs and actions. Yet, amidst this enthusiastic anticipation, it’s crucial to examine the potential pitfalls that might … Read more
Last month, The New York Times claimed that tech giants OpenAI and Google have waded into a copyright gray area by transcribing the vast volume of YouTube videos and using that text as additional training data for their AI models despite terms of service that prohibit such efforts and copyright law that the Times argues … Read more
💡 Note that this is the 3rd and final article in the series of VLMs for data extraction. You can find – the one about surveying VLMs here, and – evaluating VLMs on your own dataset here Introduction If you’re beginning your journey into the world of Vision Language Models (VLMs), you’re entering an exciting … Read more
In the years since Gartner last released a Magic Quadrant for Data Science and Machine Learning (DSML), the industry has experienced massive shifts. DataRobot has also transformed dramatically from where we began to where we stand today. The rapid pace of AI advancement is unparalleled, and at DataRobot, I’m most proud of our ability to … Read more
As AI continues to advance at a rapid pace, developers are increasingly turning to AI-driven development (AIDD) to build more intelligent and adaptive applications. However, using natural language prompts to describe complex behaviors to AI can be a real challenge. While natural language is expressive, it lacks the structure and efficiency needed to clearly communicate … Read more