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The hidden barrier to AI transformation: connectivity

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Artificial intelligence (AI) promises to bring higher productivity and lower costs to enterprises. However, despite many companies trialing the technology, it is yet to be widely adopted, with IBM finding that just 25% of AI projects had delivered the expected return on investment.

To understand why, we need to look at what all modern technology relies on, connectivity. Without the correct infrastructure in place, even the most sophisticated technologies will fall short.



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Not just giving the answers :: WRAL.com

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When most people think of AI, they think of chatbots like
Chat GPT and Gemini.

On Monday night, tech leaders are trying to get the word out about a
new form of AI called agentic. Some say we’ll end up engaging
with this technology the most.

Duke professor Jon Reifschneider built his own model that he
believes could be a gamechanger for researchers. He spoke with WRAL News about the rise of the technology and what may lie ahead for its use in daily life.

Reifschneider and cofounder Pramod Singh have a new AI product called Inquisite. They believe could be a game-changer for researchers. 

“Our ultimate goal with this is to speed up discovery and
translation so we can do things like bring new drugs to market,” Reifschneider said. “In, let’s say, 3-to-5 years rather than 10-to-20 years … We need it.”

Before showing how it works, let’s have a quick vocabulary
lesson. 

Popular chatbots like Chat GPT or Gemini are mainly
considered generative AI. That means you give it a question or prompt – and it gives you a
response based on the massive amounts of data it has access to.

Inquisite is something different. It’s referred to as agentic
AI. 

Agentic AI doesn’t just give you answers, it performs tasks
for you.

“Agents are particularly exciting because they can actually
sort of do work, very much like a human might,” Reifschneider said.

Inquisite’s agents play the role of research
assistant – scouring through its massive database of research and medical
journals to find, read and summarize the relevant papers scientists need to do
their jobs. 

“We can see here it found 119 papers that were potentially
relevant using those queries,” Reifschneider said. “It then went through a process where it reviewed
all the metadata, the titles, authors, and abstracts and it filtered those 119
papers down to just 17 papers that it determined were highly relevant to answer
my question.”

“So if you’re saving time, does that mean you get discoveries faster?” Reifschneider said. “We believe so. That’s our ultimate goal with Inquisite.”

That could mean a faster path to a cure for certain
cancers – or a new gene therapy for Parkinson’s. 

Inquisite is ahead of the curve – with the top minds in tech
this summer proclaiming agentic AI is the future.

Tech leaders have acknowledged agentic AI’s capabilities and the likelihood of future use.

“Agentic AI is real,” said Nvidia CEO and President Jensen Huang. “Agentic AI is a giant step function from
one shot AI.” 

“I think every business in the future will have an AI agent
that their customers can talk to in the future,” said Meta CEO Mark Zuckerberg. 

But will these agents replace jobs? 

“They’re really designed to augment human research teams, not
try to replace the scientists and researchers,” Reifschneider said. “That’s kind of key. You’re not
building this to replace researchers. You’re building this to help them. That’s
right, research is a highly creative task.”

When asked about AI agents potentially
taking jobs, he said he thinks fears about AI taking jobs are overblown.

In fact, he’s teaching his graduate-level students that they have a
quality AI can’t replace.

“I don’t think AI will have the creativity we need to do really novel research, I think we very much still need human scientists in the loop,” Reifschneider said.



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How AI Is Upending Politics, Tech, the Media, and More

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In an increasingly divided world, one thing that everyone seems to agree on is that artificial intelligence is a hugely disruptive—and sometimes downright destructive—phenomenon.

At WIRED’s AI Power Summit in New York on Monday, leaders from the worlds of tech, politics, and the media came together to discuss how AI is transforming their intertwined worlds. The Summit included voices from the AI industry, a current US senator and a former Trump administration official, and publishers including WIRED’s parent company, Condé Nast. You can view a livestream of the event in full below.

Livestream: WIRED’s AI Power Summit

“In journalism, many of us have been excited and worried about AI in equal measure,” said Anna Wintour, Condé Nast’s chief content officer and the global editorial director of Vogue, in her opening remarks. “We worry about it replacing our work, and the work of those we write about.”

Leaders from the world of politics offered contrasting visions for ensuring AI has a positive impact overall. Richard Blumenthal, the Democratic senator from Connecticut, said policymakers should learn from social media and figure out suitable guardrails around copyright infringement and other key issues before AI causes too much damage. “We want to deal with the perfect storm that is engulfing journalism,” he said in conversation with WIRED global editorial director Katie Drummond.

In a separate conversation, Dean Ball, a senior fellow at the Foundation for American Innovation and one of the authors of the Trump Administration’s AI Action Plan, defended that policy blueprint’s vision for AI regulation. He claimed that it introduced more rules around AI risks than any other government has produced.

Figures from within the AI industry painted a rosy picture of AI’s impact, too, arguing that it will be a boon for economic growth and would not be deployed unchecked.



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Data analytics, AI in workers’ compensation insurance

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Rob Evans, director of claim process technology at Broadspire spoke recently on the DigIn podcast about emerging technology within workers’ compensation insurance. He highlighted data analytics and artificial intelligence (AI).

Data analytics have shown value in loss prevention as well as pre-loss and post-loss considerations, Evans said. The harnessing of big data has also allowed for more benchmarking and comparison to industry averages and best in class programs. There has been an evolution in the visualization of data in various forms, he said.

He added that applying AI to the claim process can help reimagine client claim reviews, while not overwhelming claim operations staff with notification fatigue.

“Even the best in class programs we’ve seen will inevitably have some room for additional improvement. The only constant is change. So even if you’ve got things optimized, you got to really stay on top of things. And this is where bringing in the AI component is super helpful when it comes to any improvement opportunities.”

With the evolution of data visualization and analytics, there is also an ability to drill down and uncover opportunities, which can allow for more targeted investment

“When we talk about AI, I like to think of the claims process like cooking where AI provides some of the ingredients for the various recipes. … Now there’s lots of other AI ingredients too, but predictive models and LLMs are providing a couple of the key ingredients that we use to serve up quality claim outcomes. Continuing my corny food metaphor here, people at a restaurant like to order up different dishes or want some customizations made to their order. So if we think of data analytics as a menu, AI lets us think about ways to create the most delicious dish we desire, like finding litigation or closure opportunities that align with achieving the executive’s concept of success,” Evans said.

Listen to the full podcast here.



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