Here’s a brief video look at some of the advanced technology trends we’ve been watching in top web journals and our own humble Progressive Gauge Blog – analyzing current activity based on experience over 20 years in the computer trade press, now called media. We start of*f with discussion of Quantum computing that is moving subatomic waves/particles.
Archives for September 2022
How well can Nvidia tread the Agglomerverse?
Nvidia has worked hard to emerge from the worlds of graphic cards, gaming, and bitcoin mining to become a potent presence in enterprise AI considerations. It also is poised to play as a key vendor in the Metaverse, an AR-imbued but ill-defined repository for the next version of the Web.
More work is in store now as the GPU company – like most companies of any sort – navigates a more difficult economic environment – one where macro winds auger a possible enterprise spending slowdown. Already, Nvidia CEO Jensen Huang has led his crew into spaces others could not imagine.
Graphic Processing Units (GPUs) support ultrahigh memory bandwidth applications. They can churn through neural networks and sundry matrix multiplications like banshees. Huang and company pursue all their possible uses, and created a large portfolio of use cases, even as would-be competitors nip at their heels with more specialized offerings.
Visionary Huang, who we heard last week in keynotes and press conferences related to Nvidia’s GTC 2022 event, calls Nvidia an “Accelerated Computing Company.” And, he has set out to exploit “the Full Accelerated Computing Stack.”
These ambitions take form in a true slew of new offerings – ranging from the Nvidia DLSS3 deep learning sampler to GeForce RTX Series GPUs for neural rendering to Omniverse Cloud Services for Building and Operating Industrial Metaverse Applications, the Omniverse Replicator for synthetic data production and the 2,000-TFLOPS Thor SOC. The latter is probably well-described as “a super chip of epic proportions.”
Nvidia was early to see the possibility that AR/VR technology could drive a more interactive world-wide computing environment. The company coined it “the Omniverse” but now it’s joined others in the “metaverse” quest. For now, the metaverse is a loose agglomeration (the ‘Agglomerverse’?) of such elements as physics simulation, digital twins, and, of course, AI modeling. This puts Nvidia in competition or what Sam Alpert called coopetition with a host of other vendors. Hype vastly surpasses reality in today’s metaverse and the pay-off is both unclear and distant.
Meanwhile, Enterprise AI has found a place in data centers, and Nvidia has established a genuine foothold there. Obscured in the rush of GTC 2022 product announcements were less-than-flashy Apache Spark accelerator technology and AI inference announcements that may show up in revenue reports sooner than metaverse cases. Huang, for his part, sees the two technical domains playing off one another.
Be that as it may, in the metaverse and enterprise AI alike, Huang needs boots on the ground. These undertakings need great advances in skilling around big data.
It remains to be proved that corporations are anymore ready now to take on enterprise AI and the metaverse with imagination and execution. Can they imagine and execute on par or better than they did with Big Data Hadoop beginning ten years ago?
It’s worth noting that GTC 2022 software tools announcement were as proliferate as hardware news, showing the company is seeking ways to simplify the way to such advancements. Nvidia will likely need to take on greater headcount, and forge more mega-partnerships like one announced with Deloitte last week, if it going to successfully seed enterprise AI and metaverse apps.
Like most, Nvidia’s stock has been in free fall. But some of its challenges are unique. When US Government policy looked to slow down or block the transfer of advanced AI to China, Nvidia felt the brunt of it.
Meanwhile, the general rout of crypto currency impedes chip sales to crypto miners – and, as some news reports have it, a recent 2.0 update to the Ethereum blockchain takes a new proof-of-stake approach to processing and reduces the general call for GPUs for mining.
At the same time, the gaming card market has gone from famine to glut in the 24-month-plus period following the start of the global COVID pandemic. Moreover, the cost of these ever-bigger and more functional chips goes up-up-up, emptying gamer’s’ coffers.
Successes in these areas gave Nvidia wiggle room as it pursued enterprise AI. The wiggle room gets smaller just as the metaverse and enterprise AI to-do list gets taller. Among this week’s slew of portfolio additions there are some parts that will find users more quickly than others, and its up to Nvidia to suss those out and ensure they prosper. – Jack Vaughan
What’s it take to make #Metaverse real? [asks @deantak ]. In #GTC22 presser, Jensen discusses GDN – that is: a global Graphics Delivery Network – and notes as analog #Akamai Content Delivery Network (CDN). He said: “We have to put a new type of data center around the world.” pic.twitter.com/6Ur8IFwGJ3
— Jack Vaughan (@JackIVaughan) September 21, 2022
Jensen: We have a rich suite of domain specific application frame works. Now we need an army of experts to help customers apply these AI frameworks to automate their businesses. [Cue Deloitte soundtrack.] https://t.co/XBGewQGALP
— Jack Vaughan (@JackIVaughan) September 21, 2022
Omniverse Replicator — enables developers to generate physically accurate 3D synthetic data, and build custom synthetic-data generation tools to accelerate the training and accuracy of perception networks. https://t.co/t8HnVWvCcT
— Jack Vaughan (@JackIVaughan) September 20, 2022
Tech segments merge and fork
The Skeptical Examiner. Tech Industry segments merge and fork in generally obscure ways. That can be driven arbitrarily by the categorization strategies that work for analyst groups like Gartner or IDC, but it’s also driven by the fact that technology buyers don’t live in categories convenient for marketers.
Among vendors’ deflection strategies in interviews is this: “You are comparing apples and oranges.” The implication: They have no competition.
No competition if the world is in neat compartments.
In the fruit section of any supermarket you will find people grabbing apples, oranges, blueberries, bananas; I’ve never seen anyone grab a cumquat. And tech buying can mirror this wanton buyer promiscuousness.
That occurs today while looking at IDC’s Market Glance that looks at the High Performance and Performance Intensive Computing sectors. The sets and subsets thereof are subjective and various … and often collide.
The cursory viewer may be surprised by the extent to which Nvidia, and IBM compete here and there. That says something about IBM’s challenges, which, obviously, come from more directions than just Nvidia.
On the Nvidia side, it tees up a question as to whether or not the chip and tools maker can support multiple efforts successfully, as it looks to break out of the gamer-crypto space, and to thrive in the new vistas of AI.
IBM’s focus on AI, which arguably seeded the wide renewed interest in the area, seems back-burner stuff for now – as it dims down the hype machine that was Watson.
Is ‘AI’ another name for high-performance computing?
I know the Nvidia/IBM angle on this IDC chart (above and below) surprised me. As one wag said: Check with your ophthalmologist before viewing it. – J.V.
.@IDC‘s Market Glance for Performance Intensive Computing. The convergence of HPC w/ AI, Big Data, Data Analytics, and Quantum Computing brings consolidation of infrastructure bringing decades of HPC’s best practices into the forefront to achieve optimal price/performance! pic.twitter.com/N6r5c0m2F6
— Matt Eastwood (@matteastwood) September 13, 2022