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Trends in AI: Should You View Data as a Product?

Planview

Historically, companies had two approaches to deriving value from data. Some companies used a grassroots approach, where individual people and teams mined their own data stores for insights as needed. Neither can handle the amount of data coming in from customers and internal operations. The problems with those approaches?

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How to Use Generative AI and LLMs to Improve Search

TechEmpower Innovation

Moreover, LLMs come equipped with an extensive knowledge base derived from the vast amounts of data they've been trained on. For businesses, this means tapping into a broader informational spectrum without the need for manual data entry or updates. Broadly speaking, data can be categorized as either structured or unstructured.

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Unlocking Developer Productivity (and Happiness) with AI: GitHub’s Scott Densmore

Planview

Join Dr. Mik Kersten, CTO at Planview, and Scott Densmore, VP of Engineering at GitHub, in dreaming about this realistic vision for the future in this Mik + One podcast episode. They’ve spent months developing Copilot and training it on numerous coding languages. Who is Scott Densmore?

CTO 64
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Choosing Your AI Use Case: A Prioritization Framework

Planview

Dr. Rich Sonnenblick, Chief Data Scientist at Planview, warned against choosing solutions merely because they have AI in their title or seem on trend right now. Rich laid out the hidden ongoing costs: The cost of the support and maintenance over time that it takes to train the AI model continually.

CTO 64
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Forms Automation using Azure Form Recognizer

Acuvate

It automates information extraction to allow businesses to focus their time and energies on leveraging actionable insights and building cognitive document management systems instead of just compiling the data. Enjoy the benefits of pre-trained models that derive valuable information from common document types, such as invoices and IDs.

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A Brief History of AI: From Neural Networks to ChatGPT

Planview

Even the boldest of these experiments were narrow in their expertise and prohibitively expensive to train, falling far short of the hype and tainting the AI label. Corpus The internet provided an unprecedented repository of digitized text, crucial for training LLMs, albeit not without controversy regarding data usage.

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Corporate Venture Capital’s Role in Innovation (Part 5): Crucial Lessons to Strengthen CVC Success

Corporate Innovation

In addition, based on the data PwC and the NVCA have collected , the per-investment amount contributed by CVCs has increased. By analyzing the data collected from the first group, I tried to understand the lessons they learned over the years and how they impact their current investment and operating approach as corporate innovation enablers.