The pandemic significantly widened the attack surface for many organizations, due to a surge in the number of endpoints and amount of data organizations found themselves protecting. However, the creation and collection of more data from these new endpoints has magnified the opportunity for innovation.
Some organizations aren’t yet equipped to realize the potential of the data at their disposal. Companies may encounter obstacles when attempting to unlock the value of that information and use it to accomplish their business objectives.
“Transformations are not trivial things. They require vision. They require discipline and adaptability,” said Pradeep Kumar, senior vice president and general manager of HPE Pointnext. “We work closely with many of you on your transformations. So, we see firsthand the challenges you face and the opportunities right in front of you.”
The Future Calls for Distributed Environments
Also speaking at the conference, Neil MacDonald, senior vice president and general manager for HPE Compute, said HPE “can tailor your compute and supercharge your digital transformation. Market data shows us that most of you are investing to digitally empower and enable your frontline workers with data, artificial intelligence and security, extending their productivity, adaptability and their decision-making in the face of all of these rapid changes.”
WATCH: See how automation and security can aid in digital transformation.
MacDonald claimed that, in the years ahead, organizations will need to operate in much more distributed environments that embrace edge and hybrid computing that can be deployed and consumed everywhere. “To help you thrive in the future, we at HPE have been rethinking computing, meaning we want your digital transformation experience to be a success, financing to deployment,” he said.
“Regardless of your workload, we are transforming your experience. Whatever infrastructure you’re using, we’re radically simplifying your compute management,” MacDonald said. He noted HPE’s announcement in May of its Data Services Cloud Console, followed by the introduction this week of the new Compute Cloud Console.
“You can get back to managing your business instead of managing your infrastructure,” he said. “Compute Cloud Console is the cloud-based service within HPE GreenLake that empowers your organization to transform faster. It provides unified compute operations to the service, automating complex operations in a simplified experience across edge to cloud to accelerate your speed and agility.”
HPE Acquisition of Determined AI to Leverage the Value of Data
Just prior to the beginning of the conference, HPE announced it had acquired Determined AI, a San Francisco-based startup. In a June 21 press release, the company revealed its plans to “combine Determined AI’s unique software solution with its world-leading AI and high performance computing offerings to enable ML engineers to easily implement and train machine learning models to provide faster and more accurate insights from their data in almost every industry.”
Justin Hotard, senior vice president and general manager of high performance computing and mission-critical solutions at HPE, said in the press release, “AI-powered technologies will play an increasingly critical role in turning data into readily available, actionable information to fuel this new era. Determined AI’s unique open-source platform allows ML engineers to build models faster and deliver business value sooner without having to worry about the underlying infrastructure.”
At HPE Discover, Evan Sparks, CEO and co-founder of Determined AI, explained his company’s offerings this way: “What we provide is a software platform that’s really designed to help machine learning engineers and data scientists focus on the task of model development and building their machine learning models, rather than learning the entire stack of technologies required to deliver that value.”
“They don’t need to be fussing around with how to configure a graphics processing unit and high-performance networking and storage,” he continued. “Instead, we give them a layer of abstraction that lets them focus on that modeling, gives them features like high-performance parallel distributed training events, hyperparameter optimization, metrics tracking that can enable reproducibility and collaboration, all in a seamless package. And it’s fundamentally helping them deliver machine learning–powered solutions on the order of days or weeks, as opposed to years or never.”
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