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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

3) How do we get started, when, who will be involved, and what are the targeted benefits, results, outcomes, and consequences (including risks)? encouraging and rewarding) a culture of experimentation across the organization. Do not covet thy data’s correlations: a random six-sigma event is one-in-a-million.

Strategy 290
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How Svevia connects roads, risk, and refuse through the cloud

CIO Business Intelligence

Digital alerts Another project deals with slow-moving vehicles, something that increases the risk of accidents on the roads. Not for experiments For a company like Svevia, there’s no room for experimentation, underlines Wester. “We This is fairly young technology and we’re at the forefront of the world,” says Bäckström.

Risk 98
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Camunda simplifies process automation with new AI-powered natural language features

CIO Business Intelligence

Announced at its CamundaCon 2024 event in Berlin this week, the company’s pitch for AI is that the technology will hugely simplify the steep learning curve that comes with the setup phase of many business orchestration projects. This has led to big claims that run the risk of hype and disappointment down the line.

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How AI Can Supercharge Your Ransomware Defense In 2022?

Smart Data Collective

AI can protect you in the event of these and other attacks. The decisions are based on extensive experimentation and research to improve effectiveness without altering customer experience. With AI, the risk score for a device doesn’t depend on individual indicators. Predicting If a Device Is at Risk.

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7 steps for turning shadow IT into a competitive edge

CIO Business Intelligence

Ask IT leaders about their challenges with shadow IT, and most will cite the kinds of security, operational, and integration risks that give shadow IT its bad rep. That’s not to downplay the inherent risks of shadow IT.

IT 137
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Rapid AI Iteration, Reducing Cycle Time: Key Learnings from the Big Data & AI World Asia Conference

DataRobot Blog

At the well-attended data science event, a DataRobot customer panel highlighted innovation with AI that challenges the status quo. At the event, a financial services panel discussion shared why iteration and experimentation are critical in an AI-driven data science environment. Closing the Value Gap: Reducing AI Cycle Time.

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Success Stories: Applications and Benefits of Knowledge Graphs in Financial Services

Ontotext

M&A events, role changes, etc.) Let’s consider an example about risk and opportunity event detection. So we perform large scale Named Entity Recognition of company, locations and people, and we add some topics/events. Experimentation with different technical analysis services becomes possible.