VentureBeat’s AI section has been in the news lately, and Wiggers’ work has been cited by several publications. However, many readers have questions about Wiggers’ ethics and work. Is he really an expert in the field? Read on to find out.
Wiggers writes about artificial intelligence for VentureBeat
Kyle Wiggers is a senior reporter at TechCrunch with a special interest in artificial intelligence. His writing has also appeared in Digital Trends, VentureBeat, and a number of gadget blogs. He lives in Brooklyn with his partner and dabbles in piano occasionally.
Wiggers covers the world of technology and the business of technology, focusing on venture capital funding and Silicon Valley startups. He has written about product-market fit, marketing and fundraising for tech startups. His articles have also featured Superhuman founder Rahul Vohra. The first edition of TechCrunch was published in 2005.
AI is a hot topic for tech companies and investors. The rise of artificial intelligence is changing the way we live. Robotics companies are using AI to do our jobs. While robots may be a step toward automation, humans need advanced solutions to improve our health and wellbeing.
AI is a promising technology that can increase company productivity and revenue. For instance, Pizza Hut is using AI to update its technology. In the future, 80% of tech products will be built by non-technical people. AI can be trained to learn how to understand written responses from customers.
Wiggers is a freelance tech journalist with several publications under his belt. He has written about cybersecurity and data privacy issues for Wired, and his work has appeared on The State of AI Report, Wired, and the New York Observer. Sage has also written on the state of AI.
Several states are now trying to regulate AI. The Washington state is currently trying to pass Substitute House Bill 1655, which would prohibit the use of AI in discriminatory ways. Moreover, California, the leading state-level tech regulator, has introduced a bill requiring software developers to disclose the disparate impact on human beings.
AI is already making a big impact in financial services. This industry is notorious for seeking every edge and is using artificial intelligence and machine learning to help it stay ahead of the competition. Nevertheless, a recent deal between Nvidia and Arm has been delayed. The deal was halted by regulators and the CEO declared that it had “given it our best shot” – even though the deal is now off. Despite this, Nvidia announced a record fourth quarter revenue of $764 billion, an increase of 53%.
Wiggers stands behind VentureBeat’s ethics statement
Kyle Wiggers is a senior reporter at TechCrunch. He has previously written for VentureBeat, Digital Trends, Android Authority, Droid-Life, and XDA-Developers. He lives in Brooklyn with his partner and enjoys playing the piano.
Wiggers’ work has been cited in publications
Wiggers’ diagram of the heart has been cited in many publications as a fundamental tool for teaching the cardiac cycle. Its step-by-step nature makes it essential for understanding cardiac function. Wiggers detailed these steps in a 1921 publication and his graphic depiction has since become the standard way to teach the cardiac cycle.
The Wiggers diagram illustrates the pressure changes that occur in the heart throughout the cardiac cycle. Unfortunately, many students struggle with relating anatomical images to the changes in pressure. Students often confuse the cardiac cycle with the flow of blood. This can be a serious mistake.
Skael is the brainchild of Baba Nadimpalli, who previously founded financial software developer MAK Software Solutions and network tech consultancy CommCube. The goal was to create a platform that uses technologies spanning natural language processing, natural language understanding, and machine learning to automate tasks, dynamically interpreting data without deep human involvement.
“Automation is the fastest-growing enterprise technology segment, and its demand is only increasing due to a combination of macroeconomic factors,” Nadimpalli told VentureBeat via email. “It’s typical to measure return on investment in years, requiring very specific technical resources — both software and people — to design, develop, deploy, manage, and train end-to-end automation strategies … [But] implemented well, automation serves the enterprise purpose of business continuance [and unlocking growth.]”
In practice, Skael offers automation tools designed to tackle particular tasks, like refreshing and moving deals through customer relationship management software. One of Skael’s tools, for example, automates HR onboarding, offboarding, and employee assessments by updating popular HR applications. Another learns from existing IT service tickets and knowledge bases to help users order equipment and access new software.
Beyond this, Skael claims its platform can process PDFs and text-based documents such as contracts, training materials, and HR policies to search for answers to, “open domain” questions through “cognitive search.” Cognitive search — a technology that’s gained increased attention recently, prompting tech giants Microsoft, Amazon, and Google to invest in its development — uses AI to ingest, understand, organize, and query digital content from multiple data sources at once.
“Modern-day work for the vast majority of the world is a copy-and-paste of the industrial revolution, burning employees out in jobs that have very little need for human intelligence, ingenuity, or creativity,” Nadimpalli told VentureBeat via email. “Instead of wrapping people around process and then around technology, it should be the other way around, with technology wrapped around people — [and] with process as the middle layer … Skael’s platform [pushes] out the design, development and deployment of digital employees to non-technical users, [resulting] in more engaged human employees and customers [whose] time is now spent on more purposeful and engaging work.”
“Organizations in every region and industry are automating at least some business processes, yet only a slight majority have succeeded at meeting their targets,” McKinsey analysts wrote in a 2018 report. “[Specific] practices best support a successful automation effort: making automation a strategic priority, deploying technologies systematically, decentralizing governance, ensuring the IT functions’ involvement, internalizing automation’s costs and benefits, and prioritizing workforce management.”
The top reasons they cited were struggling to adapt with the technology, failing to understand how AI would change anything, difficulty integrating automation with existing IT deployments, and the need to change IT culture and app.
