Why Investors have to Appreciate the Diversity of AI 

In this contributed article, Steve Schmidt, General Partner at Telstra Ventures, offers a brief glimpse at how quickly AI innovation is spreading and advancing, and it’s a sign of what’s to come. AI is a once-in-a-generation technology, and its role in our lives and businesses will only continue to grow – often in ways that we can’t possibly imagine today.

The Three Greatest Areas of Impact for AI in Automation

In this contributed article, Jakob Freund, Co-Founder and CEO at Camunda, explores three different types of AI that he predicts will dominate industries as organizations work to ensure business processes are streamlined and working as intended. These three AI buckets include predictive decision-making, generative processes, and assistive tools.

26 Years Since its Inception, Postgres is Just Getting Started 

In this contributed article, Charly Batista, PostgreSQL Tech Lead at Percona, explores why Postgres is on the rise and why Postgres’ brand of open source is good for business.
One of the most widely used database management systems in the world, Postgres still lags quite substantially behind the likes of MySQL and Oracle in total adoption.

How Enterprises Can Rise Above Data Gravity for a Better Life in the Cloud

In this contributed article, Jim Liddle, Chief Innovation Officer at Nasuni, describes how having file data stored in the cloud and workloads on-premises can result in serious performance issues because remote access and data consolidation don’t play well together. In fact, the combination can create “data gravity” that complicates and slows the movement of data, worsened by the latency that often accompanies remote access. The resulting lack of speed and flexibility presents significant issues when decisions must be made in seconds in order to prevent potential loss or generate revenue to the tune of millions of dollars.

Cash Treasury Trading in the Age of AI

In this contributed article, Shankar Narayanan, Head of Trading Research, Quantitative Brokers, discusses how In the era of artificial intelligence, cash treasury trading presents a unique opportunity to integrate new technologies, enhance trading methodologies and meet the growing demands of a rapidly evolving market. 

Regulate the Use Cases—Not AI Itself

In this contributed article, CF Su, VP of ML, Hyperscience, agrees that regulation is needed, but as opposed to sweeping oversight, he supports regulating specific uses of AI, such as licensing the business applications of AI models rather than requiring licenses for creating them. This targeted, tactical government oversight will close the trust gap between the public and AI, which is his #1 concern currently facing the technology’s adoption.

Secret to Building Killer ChatGPT Biz Apps is Traditional AI 

In this contributed article, Gaetan Castelein, VP of Marketing at Tecton gives focus to Predictive AI vs. Generative AI and points out that AI is still in its infancy as a business application. It’s important to remember that no matter what transpires between generative AI and predictive AI, there is no road forward without making available to both models the highest-quality data. 

Navigating Data Lake Challenges: Governance, Security, and GDPR Compliance

In this contributed article, Coral Trivedi, Product Manager at Fivetran, discusses how enterprises can get the most value from a data lake. The article discusses automation, security, pipelines and GSPR compliance issues.

Who’s to Blame for the Data Capability Wall?

In this contributed article, Cameron Benoit, Director of Solution Consulting, Adverity, explores why data technology solutions keep stalling before takeoff. With cloud innovation making it easier
than ever to amass vast collections of specialist tools, businesses theoretically shouldn’t be
short on any capabilities. The problem is, prioritizing enticing features over functionality is
creating data infrastructure that’s flawed at best or unfit for purpose at worst. To avoid
running into capability walls, careful tech selection and stack building is key.

The Do’s and Don’ts of Data Monetization

In this contributed article, Dan Lynn, Senior Vice President of Product at Crux, believes as others have pointed out, data may be the new oil in the sense that it’s a valuable commodity that has fueled economic growth in the 21st century. But unlike dwindling oil stocks, the amount of data is only growing, and it’s reusable. So if you’re considering a data monetization program, keep these do’s and don’ts in mind and reuse your organization’s valuable data to generate even more value.