In The Press

ReWorked: Do we collaborate too much?

Last year my firm Deep Analysis ran a survey that asked 500 people working in U.S. software firms about their work from home and hybrid work experiences, focusing on collaboration systems. Back in the day, meetings had agendas, minutes were taken, and action items were assigned to individuals. Pretty basic stuff, if a pain in the backside to do. Even so, most meetings were at least focused, action-oriented and generally productive. Today, many online meetings are none of the above, with multiple attendees wondering why they are there at all. Long story short, a majority of people in our survey were fed up with dealing with the numerous pointless and confusing meetings.

TechTarget: Lack of competition is driving federal budget antitrust hike

In other areas, the White House is adding $187 million to the National Institute of Standards and Technology for research initiatives and the development of standards to accelerate the adoption of emerging technologies such as quantum science, advanced biotechnologies, and artificial intelligence. But the funding increase is too little, too late, said Alan Pelz-Sharpe, founder of market research firm Deep Analysis. Pelz-Sharpe said it would be good for the U.S. to set standards for AI, particularly around the areas of fair use, transparency, and bias. However, he said the U.S. is behind the curve when it comes to standards-setting and likely won’t set a precedent for the rest of the world to follow. The international community has already moved ahead to define and set standards. Alan Pelz-SharpeFounder, Deep Analysis “The international community has already moved ahead to define and set standards,” Pelz-Sharpe said.

TechTarget: Chinas new AI regulations

Learning from China’s approach  Though it may be “counterintuitive” to give China credit regarding its AI regulations given the political climate, Pelz-Sharpe said its rules “set a new benchmark that may drive improved regulations elsewhere.” The AI regulations outlaw algorithmic price gouging and require an explainable algorithmic decision-making process. The algorithms have to be “trustworthy AI,” meaning built and tested to be as fair, explainable and bias-free as possible, Pelz-Sharpe said. While there are discussions about trustworthy AI in areas such as Europe and the U.S., Pelz-Sharpe said there’s little from a regulatory standpoint when it comes to defining the phrase. China, he said, is “making this concrete.” “Beyond blatant and deliberate misuse of AI, two of the biggest factors of concern for its use are bias and explainability,” he said. “These regulations at least attempt to address some of these concerns.”

KMWorld: Knowledge Unchained

The use of blockchain for information management will never compete for eyeballs as Mrs. Trump does. Nevertheless, developers and enterprise innovators are actively exploring and beginning to use blockchain under the radar. I’ll leave the “how” of the underlying technology for another day. In this article, I want to focus on the fundamental conceptual reasoning behind using blockchain for information and knowledge management.  Blockchains only do one thing, which can be hard to get your head around. Blockchains eliminate the need to trust other people. That’s it; that is all there is to it. Under the covers, there is some very complex technology, underlying security, and math. But in practical business terms, blockchains remove the need to trust other people, companies, partners, or suppliers when they tell you something or give you a document. Trust is deferred to the system itself.  With a blockchain, you all have the same version of the “truth.” Or, to put it another way, blockchains provide a trustless system, removing the need to trust one another. 

TechTarget: Box strikes back with solid quarter

“You can share files with your Slack colleagues, but keep the security and compliance levels that you have from your Box environment,” said Deep Analysis founder Alan Pelz-Sharpe. “It takes the power of the content cloud and brings it into the collaborative environment of Slack, which is super powerful.”

Yahoo Finance: Veritone Launches AI-Driven Intelligent Distributed Energy Resource Management Solution (iDERMS)

“Veritone’s launch of the intelligent distributed energy resource management system (iDERMS) addresses head-on the challenges of green energy,” said Alan Pelz-Sharpe, founder of analyst firm Deep Analysis. “With green energy’s inherent unpredictability, there is a clear need for AI-powered predictive energy solutions to balance supply and demand, lower energy costs and ensure grid reliability and resilience in the face of our fragile grid infrastructure.”

TechTarget: Box Integration with Slack

“You can share files with your Slack colleagues, but keep the security and compliance levels that you have from your Box environment,” said Deep Analysis founder Alan Pelz-Sharpe. “It takes the power of the content cloud and brings it into the collaborative environment of Slack, which is super powerful.”

TechTarget: IBM offloads Watson Health business data, analytics

“It comes as no surprise at all as Watson Health was described long ago by IBM as a moonshot, but it failed to take off,” said Alan Pelz-Sharpe, founder of Deep Analysis. “That it has been sold to an investment firm means that this is likely not its final resting place, but will likely be tidied up, restructured and then resold at a later date.” The sale of the Watson unit could foreshadow IBM selling off more of its divisions and technology assets, Pelz-Sharpe said.

Big Data Quarterly: AI and Automation Bring Opportunities—And Challenges

In other words, what worked in the late 1990s and early 2000s does not work so well today. Now, we live in an agile world; we live in a world where we all have had to accept and deal with unexpected upheaval and change. There is a dawning realization that business process activities need to be equally agile and adaptable; few have any appetite to be locked in again to a fixed way of working. Business attitudes and approaches to automation are also evolving, embracing a philosophy of adaptable, beneficial, and affordable over the now-dated philosophy of faster, cheaper, and better. Although the organizations I talk to in both the public and private sectors understand that, albeit often unconsciously, it’s a more difficult shift for technology vendors to embrace.

LeMagIT(France) AI: a certain awareness of the consequences on the environment

Businesses can get carried away with the idea that they need an advanced deep learning system that can do it all, according to Alan Pelz-Sharpe. However, if they want to tackle a targeted use case, like automating an invoicing process, they don’t need an advanced system. These systems are expensive and use a lot of data, which means they have a high carbon footprint. A specialized system will have been trained on a much smaller amount of data while still being capable of fulfilling a specific use case just as well as a more general system. “Because it is highly specialized, this AI has been trained on the most precise data possible” while keeping a small set of data, says Alan Pelz-Sharpe. A deep learning model , on the other hand, has to stir up massive amounts of data to achieve anything.

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