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MLPerf is the definitive performance benchmark for Artificial Intelligence. The latest set of competitive performance benchmarks were released this week, and NVIDIA so dominated the benchmarks they effectively stand alone in this market right now for core functions like image classification, object detection, and machine translation. Others either didn’t have a technology ready to submit to a category, or their performance was so low to be arguably meaningless.
Let’s talk about the promise and the problems with being so far out front.
By being so dominant in this space, it places NVIDIA’s core technology at the top of any shortlist for those partnering in this area. It helps explain why Mercedes, a famous company for not accepting technology from others for critical strategic programs, partnered with NVIDIA. If they wanted a viable self-driving platform backed by deep simulation, NVIDIA was the only short term path to achieving that goal.
As a result, expect NVIDIA to gain even more partners, to dominate more industries, and to remain the definitive leader of the segment. Tactically they are unbeatable. But this kind of overwhelming leadership can lead to problems.
There are three unique problems that NVIDIA will now have to deal with, given their extreme leadership. They are false confidence, regulatory oversight, and higher than average intellectual property theft. Let’s take each in turn.
While most every major AI tech vendor (and several universities) is participating in MLPerf, it is unusual to submit results when you are well off the mark. Those not submitting benchmark results could be far better off than these latest charts indicate, and they may be far more competitive than they appear as a result.
NVIDIA, believing they are unbeatable, could falsely feel their lead is unbeatable and slow down their impressively fast development effort allowing the other firm(s) to pass them and then be unable to keep up. While there is no evidence I can see that NVIDIA is slowing down, the risk remains very real. A closer ranked competitor generally will help drive the leader to ever-higher performance, something that NVIDIA will have to do itself until such a competitor emerges.
When you are effectively the only vendor capable of performing at an adequate level, you own the market. That could have anti-trust implications because of the resulting market power. We just saw Apple, Amazon, Facebook, and Google begin what will likely be a dance concluding with one or more of them being broken up (odds favor Google and Amazon being broken up, Facebook being sanctioned, and Apple being left to the States which have begun their actions).
Tighter competition generally shields the leading company from this kind of government response. Right now, NVIDIA doesn’t appear on any anti-trust action I’m aware of, but NVIDIA will need to be very careful they don’t abuse their market power to avoid being in that hot seat. NVIDIA has a decent reputation with its partners, and if they maintain that, they should be safe here, but it remains a risk.
When you are as far out ahead as NVIDIA does competitors, and particularly other countries will look to mine you for information illegally. This means everything from placing people in the company to get that information, appearing as customers rather than IP thieves to gain access to it that way.
This level of leadership in a technology area seen as a critical part of the next industrial revolution will be an extremely attractive lure that many may not be able to resist. NVIDIA needs to be able to share its technology with customers (it has sizeable open-source component) so that those customers can implement it in their products but, in so doing, will increase the likelihood of IP theft, meaning the firm will need to be extraordinarily vigilant.
When it comes to core AI technology, NVIDIA remains the company to beat and by an impressively significant margin. However, this is based on public information, and few are sharing where they are. This can lead to several problems for NVIDIA ranging from false confidence to intellectual property theft that NVIDIA should be able to deal with if they don’t take their eyes off the ball, and NVIDIA’s CEO is known for having eyes in the back of his head.
The biggest potential problem, though, is the abuse of their market power because that is something that tends to catch every company that becomes dominant up eventually and it is the most difficult to mitigate because it means putting in place oversight which managers universally find annoying.
Right now, NVIDIA stands alone, that will change, and whether NVIDIA remains out front or not, as this market matures, a lot will have to do with how the firm anticipates the related unique threats, including typical executive behavior.
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Nvidia Tries To Rein In Chatgpt’s Overactive Imagination
Nvidia, the GPU mega weight that helps train language models like ChatGPT, has recently launched ‘NeMo Guardrails’ — an open-source software designed to keep AI chatbots on the straight and narrow.
According to the company, the software aims to keep responses on topic, improve data security, and combat random spurts of inaccurate information commonly known as AI ‘hallucinations’.
While this doesn’t satisfy the six-month AI development pause that tech leaders like Elon Musk and Steve Wozniak are calling for, it does aim to address some major issues the technology faces today.
Nvidia Releases ‘NeMe Guardrails’ to Tackle AI HallucinationAI tools like ChatGPT, Google Bard, and Bing Chat are capable of responding to just about any prompt fired at them. But this doesn’t mean their responses should always be trusted.
When put to the test, OpenAI’s ChatGPT is consistently found to give inaccurate answers, with the chatbot routinely failing at basic math, going off script, and spouting out content that seems straight-up implausible.
Nvidia — the supercomputing giant that’s responsible for training AI tools like ChatGPT — is aware of its tendency to hallucinate and has created NeMe Guardrails in an attempt to improve the accuracy and safety of the technology.
“Safety in generative AI is an industry-wide concern. NVIDIA designed NeMo Guardrails to work with all LLMs, such as OpenAI’s ChatGPT.” – Nvida blog post
NeMe helps developers make sure language models stick to their requirements by helping them to instate topical, safety, and security guardrails.
In Nvidia’s own words, the software’s topical rails aim to ‘prevent apps from veering off into undesired areas’, while its security guardians ‘ensure apps respond with accurate, appropriate information’.
Finally, its security guardrails work by preventing the tools from connecting to unsafe third-party apps that may be culpable of compromising private information.
But how does the software limit chatbot delusion? According to Nvidia, the software uses a second logic learning model (LLM) to fact-check the answers of the first one. If the second LLM doesn’t come up with matching answers, the response is deemed to be a hallucination before it’s sent to the user.
Who Can Use NeMe Guardrails?Since NeMo Guardrails runs on open-source technology, its able to be used by any enterprise app developer looking to add extra safeguards to its chatbot.
Programmers are able to use the language to create custom rules for their AI model, implementing as many guardrails as they see fit.
The software is being incorporated into the NVIDIA NeMo framework which includes everything you would need to train and tune a language model and is currently available on GitHub.
Are These Guardrails Enough to Keep Users Safe?Nvidia’s new software represents an important development in chatbot accuracy.
However, while NeMe Guardrails was designed to keep AI-generated content on track while protecting users from security risks, it fails to address instances of “bias” and “deception” cited in a recent complaint to the Federal Trade Commission (FTC) by the Center of AI and Digital Policy (CAIDP).
“We look forward to the good that will come from making AI a dependable and trusted part of the future.” – Nvidia blog post
After pivoting its focus to AI technology, Nvidia has profited heavily from the explosion of tools like ChatGPT and Microsoft’s Bing Chat, meaning it’s unlikely to heed the calls of concerned voices such as Elon Musk and Steve Wozniak to slow down.
Ultimately, while some AI skeptics may fear NeMe Guardrails don’t go far enough, the software does give developers a solid framework to follow. What’s more, with the US rolling out AI controls a lot slower than its European counterparts, we think that any attempt to improve and regulate chatbot technology represents a promising step in the right direction.
Nvidia Geforce Gtx 960 Graphics Card Review: Maxwell Meets Pc Gaming’s Sweet Spot
The battle for PC gaming’s “sweet spot” has a new challenger. With the GeForce GTX 980 and 970 firmly in command of the premium graphics card market, Nvidia’s setting its sights on the crucial 1080p enthusiast segment with the GTX 960, the first truly mainstream iteration of its powerful, yet stunningly power-efficient “Maxwell” processor architecture.
Meet mainstream MaxwellLet’s take a quick, high-level look at the GTX 960’s key points before diving into real-world benchmarks.
In reference form, the GTX 960 measures 9.5 inches long, taking up dual slots in your case and packing a dual-link DVI port, an HDMI 2.0 port, and a trio of DisplayPort connections.
One other thing jumps out staring at the spec sheet: The GTX 960 features only 2GB of GDDR5 memory with a 128-bit bus, which seems… paltry, to say the least. But Nvidia says that caching improvements in Maxwell, combined with the company’s third-generation delta color compression engine, help the GM206 GPU use its memory bandwidth far more effectively than its predecessor, the GM106 “Kepler” CUDA core. As such, the “lack” of memory bandwidth wasn’t an issue in our testing, and the limited RAM isn’t likely to be an issue when you’re gaming at 1080p, a.k.a. the target use for this card.
And really, what do you expect for $200, anyway? Nevertheless, it would’ve been nice to see 3GB or 4GB of memory, or at least a wider memory bus to more effectively future-proof the card.
The Asus GTX 960 Strix, sans shroud, revealing the PCB in all its glory.
Nvidia’s Multi-Frame Anti-aliasing technology is getting a big shot in the arm with the release of the GTX 960, however. Anti-aliasing smooths out visual jaggies in games, albeit with a performance cost. MFAA delivers visuals on par with multi-sample anti-aliasing, but with far less of an impact on frame rates. Testing has shown that compared to 4x MSAA, 4x MFAA delivers roughly the same level of visual fidelity at around 8- to 15-percent higher frame rates, depending on the title. That’s none too shabby!
This Nvidia slide highlights the GTX 960’s key software features.
The GTX 960 and its GM206 chip also feature support for H.265 encoding and decoding. The GTX 970 and 980 support only H.265 encoding. The GTX 960 also supports HDCP 2.2 “content protection” over HDMI. In other words, the GTX 960 should be able to stream 4K Netflix streams like a champ—if 4K displays ever really become a big thing, that is.
Meet the Asus GTX 960 Strix and EVGA GTX 960 SSCNow let’s get into the fun stuff. We reviewed two GTX 960 samples: The Asus Strix with DirectCU II cooling and EVGA’s GTX 960 SuperSC (SSC) edition with ACX 2.0+ cooling.
The port selection on the Asus Strix is bog-standard for a GTX 960.
Remember I mentioned how coolly and efficiently the Maxwell architecture lets these new Nvidia cards run? Third-party graphics card makers are already putting that efficiency to tremendous use. Asus and EVGA’s cards don’t even activate their fans until temperatures hit 55 C and 60 C, respectively. And when you combine Maxwell’s efficiency with the custom aftermarket cooling solutions found in these cards, you won’t hit those temps often in more casual or modest games, like League of Legends, The Walking Dead, and many indie or 4x strategy games.
The Asus Strix topped out at 58 C in our tests, and that was only after applying a hefty overclock and running the Furmark benchmark, which Nvidia’s press materials call a “power virus.” The EVGA SSC hit max temperatures of around 75 C under extreme duress, but ran far cooler in normal scenarios. Both cards ran extremely quietly even when the fans were whirring, almost to the point of eeriness.
The EVGA GTX 960 Super SC.
The $210 EVGA GTX 960 SSC with ACX 2.0+ cooling measures slightly longer than a reference GTX 960, at 10.25 inches. The card packs a thick heat sink underneath its dual fans, along with a cooling plate to keep your card’s memory and MOSFET chilled, as well as straight—not curved—heat pipes, which EVGA says reduces GPU temperatures by an extra 5 C. The EVGA SSC requires an 8-pin power connector, rather than the reference card’s 6-pin. In the box you’ll find an 8-pin power cable, a DVI to VGA adapter, EVGA stickers, a poster, and a utility installation disc that includes EVGA’s PrecisionX overclocking utility.
The Asus Strix looks an awful lot like Bubo, that mechanical owl in Clash of the Titans.
The nifty-looking $215 Asus Strix resembles an owl, with thick, snaking heat pipes almost taking the place of eyebrows. It measures a bit shorter than a stock GTX 960 at 8.5 inches and it includes thoughtful touches like labeled output connections and a full metallic backplate. You’ll find a DVI to VGA converter inside its box, too, along with a disc containing Asus’ own GPU Tweak overclocking tool.
Benchmarking the GTX 960Next page: Benchmarks and more.
The Brutal Graphics War Continues As Nvidia Reveals The Geforce Gtx Titan X
The graphics war continued unabated on Tuesday, as Nvidia yanked the curtain up on its $1,000 GeForce GTX Titan X, a video card that has already been declared the new king of the gaming GPUs.
The Titan X packs a whopping 12GB of GDDR5 memory on board and more than 33 percent more shaders than the company’s current top-end Maxwell GPU, the GeForce GTX 980.
The Titan X is DirectX 12 capable and was actually powering many of the virtual reality demonstrations at the Game Developers Conference held earlier this month in San Francisco. The GPU is based on a GM200 chip which is essentially an “uncut” version of the same part used for the GeForce GTX 980. That gives the chip a full 3,072 CUDA cores, compared to the GTX 980’s 2,048. (Chip companies regularly cut or disable portions of processors for marketing, yield and pricing reasons.)
Nvidia’s new GeForce Titan X has been crowned the new king of gaming GPUs.
That 12GB of RAM is the real eye opener, as no consumer-level, single-GPU graphics card has packed that much RAM before. While seemingly excessive, the 12GB of RAM allows the card to operate at ultra-high resolutions and with crazy amounts of memory-hogging image filtering.
In fact, our review—which you can read right here—validates Nvidia’s claim that the Titan X is the first single-GPU card capable of playing top games at 4K resolution and high graphics detail settings. It also easily bests the top single-GPU cards from AMD and Nvidia’s previous king, the GeForce GTX 980.
The key word here is “consumer-level,” of course. Many gamers will scoff at the mention of the Titan X even being considered a consumer card, as it will cost a premium over the GeForce GTX 980 card already available for $550 and up.
Pricing TBD and leaks aboundPricing is another touchy matter for the Titan X. Despite dropping a bomb by surprise announcing the card at the Game Developers Conference, hard details of the card were not revealed. Eventually Nvidia pre-briefed media outlets and sent out review cards, but the $1,000 pricing of the card remained a closely held secret, only unveiled to the world by Nvidia CEO Jen-Hsun Huang during his GPU Technology Conference keynote on Tuesday.
The reason for the pricing being held so closely to the vest is likely due to two factors: The first is maneuvering room in its ever-constant war with graphics chip vendor AMD. By holding the price of the GPU until the very last minute, Nvidia can react to moves by AMD, which is also preparing a new high-end graphics card.
The second reason is to prevent further leaks, as loose lips have haunted the company for its last few major GPU launches.
Despite fairly tight security, details and presentations for the GeForce GTX 980 leaked out before the official announcement. With the Titan X, during a press briefing at GDC, the press was only allowed to scribble notes of the card’s specs and capabilities rather than receiving the customary copy of the presentation given under strict non-disclosure agreement. It was supposed to minimize leaks—but the security procedures didn’t help. Specs for the Titan X as well as purported benchmarks of the card were leaked to the web over the previous weeks anyway.
Titan’s compared
Do you even Titan brah?The Titan lineup itself has always lived in an odd place between GeForce cards aimed at gamers and the Tesla and Quadro lines aimed at professional and Enterprise users.
The original Titan, for example, was released in early 2013 for $1,000, and few thought gamers would buy them. Yet the cards were surprisingly popular for the ultra-enthusiasts who just wanted to go to 11—even if doing so cost 50 percent than with a card that went to 10.
Graphics analyst Jon Peddie of Jon Peddie Research said that while it may surprise Joe Six Pack gamer griping about the card’s price on an Internet forum, ultra-enthusiast cards have sold relatively well and that doesn’t appear to be stopping.
“The Titan X is in the enthusiast class gaming AIB category. That segment has grown steadily for the past 15 years, not dramatically—a few points a year—but growing, compared to the gentle decline overall in PC sales,” Peddie said.
The GeForce Titan X in the buff reveals massive amounts of GDDR5 memory around one massively huge die.
It may actually be a value buy, or notTitans have also been surprisingly popular among developers using Nvidia’s GPU-based computing platform, called CUDA. Even at $1,000, Titans are a magnitude cheaper than the company’s Quadro and Tesla professional graphics card lines.
This value has even withstood the test of time. The original Titan, going on two-years old, can still sell for nearly its original price. Much of that comes from the Titan’s double-precision floating point performance.
Like all chip companies, Nvidia will take a chip and intentionally downgrade its performance or switch off features. For example, the GeForce GTX 980 equals the two-year old Titan in single-precision floating point performance, but its double-precision floating point performance is 144GFLOPS vs. the 1,500 GFLOPS of the now-ancient Titan.
The GM204-based GeForce GTX 980, for example, is rated at 144GFLOPS double-precision performance while the older GK110-based GeForce GTX 780 Ti is rated at 210GFLOPS. Even the standard GeForce GTX 780 aces the current top gun gaming card, pushing 166GFLOPS.
Where will the Titan X fall? Speculation that the Maxwell-based Titan X would be somewhat disappointing for compute purposes were confirmed at GTC. During Huang’s keynote, he said that the Titan X is made for single-precision floating point for performance. For double-precision, he said, Nvidia still offers the Titan Z, which packs a pair of those older, more precision-pushing GK110 chips.
Much of this may be hand wringing over nothing though. As Nvidia hasn’t introduced a professional card using the equivalent GM200 core yet, it’s possible the company has simply locked up the functionality and will switch it on when needed.
And then there’s AMDNvidia also has more to worry about from AMD.
Even though Nvidia has enjoyed a lengthy time at the top and nearly a two-to-one lead over AMD in the discrete graphics sales in recent years, it’s clear a new AMD GPU will be tipping soon. After Nvidia unexpectedly outed Titan X, AMD officials began telling the press that they had some secrets there too: One of GDC’s VR demos was being powered by the next-generation flagship Radeon card.
Like other media outlets, I asked to see the card and was denied. Even a glimpse of the back of the computer was denied. When I pointed out that for all I knew, it was a Radeon R9 290X inside, I was told to simply take them at their word for it. This picture of this intentionally sedate PC is as close as I could get to the company’s next-gen part. Gordon Mah Ung
AMD’s next-gen GPU was also secretly powering many of the demonstrations at this year’s Game Developer’s Forum.
Normally, such a move would be dismissed as saber rattling or trying to pathetically get back into the limelight after Nvidia’s surprise Titan X announcement, but the wide “I just ate the canary” grins from the AMD officials tell me it was real.
AMD hasn’t been immune from the leaks that have haunted Nvidia either. From performance benchmarks to reports of crazy amounts of memory bandwidth powered by stacked memory techniques and next-generation super wide memory buses, the problem AMD faces with its supposed Radeon 390X is uncontrolled hype. If the card doesn’t come out and offer “60 percent” more performance than its top GPU or wipe the floor with the Titan X, the public is likely to be highly disappointed even if it is a competitive GPU.
Still, today is about the GeForce Titan X. Despite the leaks, and despite fears about its compute prowess, the Titan X appears to be everything Nvidia has pitched it as so far: the world’s most powerful gaming GPU.
Nvidia’S Ai Dominance: Pros And Cons
MLPerf is the definitive performance benchmark for Artificial Intelligence. The latest set of competitive performance benchmarks were released this week, and NVIDIA so dominated the benchmarks they effectively stand alone in this market right now for core functions like image classification, object detection, and machine translation. Others either didn’t have a technology ready to submit to a category, or their performance was so low to be arguably meaningless.
Let’s talk about the promise and the problems with being so far out front.
By being so dominant in this space, it places NVIDIA’s core technology at the top of any shortlist for those partnering in this area. It helps explain why Mercedes, a famous company for not accepting technology from others for critical strategic programs, partnered with NVIDIA. If they wanted a viable self-driving platform backed by deep simulation, NVIDIA was the only short term path to achieving that goal.
As a result, expect NVIDIA to gain even more partners, to dominate more industries, and to remain the definitive leader of the segment. Tactically they are unbeatable. But this kind of overwhelming leadership can lead to problems.
There are three unique problems that NVIDIA will now have to deal with, given their extreme leadership. They are false confidence, regulatory oversight, and higher than average intellectual property theft. Let’s take each in turn.
While most every major AI tech vendor (and several universities) is participating in MLPerf, it is unusual to submit results when you are well off the mark. Those not submitting benchmark results could be far better off than these latest charts indicate, and they may be far more competitive than they appear as a result.
NVIDIA, believing they are unbeatable, could falsely feel their lead is unbeatable and slow down their impressively fast development effort allowing the other firm(s) to pass them and then be unable to keep up. While there is no evidence I can see that NVIDIA is slowing down, the risk remains very real. A closer ranked competitor generally will help drive the leader to ever-higher performance, something that NVIDIA will have to do itself until such a competitor emerges.
When you are effectively the only vendor capable of performing at an adequate level, you own the market. That could have anti-trust implications because of the resulting market power. We just saw Apple, Amazon, Facebook, and Google begin what will likely be a dance concluding with one or more of them being broken up (odds favor Google and Amazon being broken up, Facebook being sanctioned, and Apple being left to the States which have begun their actions).
Tighter competition generally shields the leading company from this kind of government response. Right now, NVIDIA doesn’t appear on any anti-trust action I’m aware of, but NVIDIA will need to be very careful they don’t abuse their market power to avoid being in that hot seat. NVIDIA has a decent reputation with its partners, and if they maintain that, they should be safe here, but it remains a risk.
When you are as far out ahead as NVIDIA does competitors, and particularly other countries will look to mine you for information illegally. This means everything from placing people in the company to get that information, appearing as customers rather than IP thieves to gain access to it that way.
This level of leadership in a technology area seen as a critical part of the next industrial revolution will be an extremely attractive lure that many may not be able to resist. NVIDIA needs to be able to share its technology with customers (it has sizeable open-source component) so that those customers can implement it in their products but, in so doing, will increase the likelihood of IP theft, meaning the firm will need to be extraordinarily vigilant.
When it comes to core AI technology, NVIDIA remains the company to beat and by an impressively significant margin. However, this is based on public information, and few are sharing where they are. This can lead to several problems for NVIDIA ranging from false confidence to intellectual property theft that NVIDIA should be able to deal with if they don’t take their eyes off the ball, and NVIDIA’s CEO is known for having eyes in the back of his head.
The biggest potential problem, though, is the abuse of their market power because that is something that tends to catch every company that becomes dominant up eventually and it is the most difficult to mitigate because it means putting in place oversight which managers universally find annoying.
Right now, NVIDIA stands alone, that will change, and whether NVIDIA remains out front or not, as this market matures, a lot will have to do with how the firm anticipates the related unique threats, including typical executive behavior.
Nvidia’S Ai Dominance: Pros And Cons
MLPerf is the definitive performance benchmark for Artificial Intelligence. The latest set of competitive performance benchmarks were released this week, and NVIDIA so dominated the benchmarks they effectively stand alone in this market right now for core functions like image classification, object detection, and machine translation. Others either didn’t have a technology ready to submit to a category, or their performance was so low to be arguably meaningless.
Let’s talk about the promise and the problems with being so far out front.
By being so dominant in this space, it places NVIDIA’s core technology at the top of any shortlist for those partnering in this area. It helps explain why Mercedes, a famous company for not accepting technology from others for critical strategic programs, partnered with NVIDIA. If they wanted a viable self-driving platform backed by deep simulation, NVIDIA was the only short term path to achieving that goal.
As a result, expect NVIDIA to gain even more partners, to dominate more industries, and to remain the definitive leader of the segment. Tactically they are unbeatable. But this kind of overwhelming leadership can lead to problems.
There are three unique problems that NVIDIA will now have to deal with, given their extreme leadership. They are false confidence, regulatory oversight, and higher than average intellectual property theft. Let’s take each in turn.
While most every major AI tech vendor (and several universities) is participating in MLPerf, it is unusual to submit results when you are well off the mark. Those not submitting benchmark results could be far better off than these latest charts indicate, and they may be far more competitive than they appear as a result.
NVIDIA, believing they are unbeatable, could falsely feel their lead is unbeatable and slow down their impressively fast development effort allowing the other firm(s) to pass them and then be unable to keep up. While there is no evidence I can see that NVIDIA is slowing down, the risk remains very real. A closer ranked competitor generally will help drive the leader to ever-higher performance, something that NVIDIA will have to do itself until such a competitor emerges.
When you are effectively the only vendor capable of performing at an adequate level, you own the market. That could have anti-trust implications because of the resulting market power. We just saw Apple, Amazon, Facebook, and Google begin what will likely be a dance concluding with one or more of them being broken up (odds favor Google and Amazon being broken up, Facebook being sanctioned, and Apple being left to the States which have begun their actions).
Tighter competition generally shields the leading company from this kind of government response. Right now, NVIDIA doesn’t appear on any anti-trust action I’m aware of, but NVIDIA will need to be very careful they don’t abuse their market power to avoid being in that hot seat. NVIDIA has a decent reputation with its partners, and if they maintain that, they should be safe here, but it remains a risk.
When you are as far out ahead as NVIDIA does competitors, and particularly other countries will look to mine you for information illegally. This means everything from placing people in the company to get that information, appearing as customers rather than IP thieves to gain access to it that way.
This level of leadership in a technology area seen as a critical part of the next industrial revolution will be an extremely attractive lure that many may not be able to resist. NVIDIA needs to be able to share its technology with customers (it has sizeable open-source component) so that those customers can implement it in their products but, in so doing, will increase the likelihood of IP theft, meaning the firm will need to be extraordinarily vigilant.
When it comes to core AI technology, NVIDIA remains the company to beat and by an impressively significant margin. However, this is based on public information, and few are sharing where they are. This can lead to several problems for NVIDIA ranging from false confidence to intellectual property theft that NVIDIA should be able to deal with if they don’t take their eyes off the ball, and NVIDIA’s CEO is known for having eyes in the back of his head.
The biggest potential problem, though, is the abuse of their market power because that is something that tends to catch every company that becomes dominant up eventually and it is the most difficult to mitigate because it means putting in place oversight which managers universally find annoying.
Right now, NVIDIA stands alone, that will change, and whether NVIDIA remains out front or not, as this market matures, a lot will have to do with how the firm anticipates the related unique threats, including typical executive behavior.
Nvidia’S Ai Dominance: Pros And Cons
MLPerf is the definitive performance benchmark for Artificial Intelligence. The latest set of competitive performance benchmarks were released this week, and NVIDIA so dominated the benchmarks they effectively stand alone in this market right now for core functions like image classification, object detection, and machine translation. Others either didn’t have a technology ready to submit to a category, or their performance was so low to be arguably meaningless.
Let’s talk about the promise and the problems with being so far out front.
By being so dominant in this space, it places NVIDIA’s core technology at the top of any shortlist for those partnering in this area. It helps explain why Mercedes, a famous company for not accepting technology from others for critical strategic programs, partnered with NVIDIA. If they wanted a viable self-driving platform backed by deep simulation, NVIDIA was the only short term path to achieving that goal.
As a result, expect NVIDIA to gain even more partners, to dominate more industries, and to remain the definitive leader of the segment. Tactically they are unbeatable. But this kind of overwhelming leadership can lead to problems.
There are three unique problems that NVIDIA will now have to deal with, given their extreme leadership. They are false confidence, regulatory oversight, and higher than average intellectual property theft. Let’s take each in turn.
While most every major AI tech vendor (and several universities) is participating in MLPerf, it is unusual to submit results when you are well off the mark. Those not submitting benchmark results could be far better off than these latest charts indicate, and they may be far more competitive than they appear as a result.
NVIDIA, believing they are unbeatable, could falsely feel their lead is unbeatable and slow down their impressively fast development effort allowing the other firm(s) to pass them and then be unable to keep up. While there is no evidence I can see that NVIDIA is slowing down, the risk remains very real. A closer ranked competitor generally will help drive the leader to ever-higher performance, something that NVIDIA will have to do itself until such a competitor emerges.
When you are effectively the only vendor capable of performing at an adequate level, you own the market. That could have anti-trust implications because of the resulting market power. We just saw Apple, Amazon, Facebook, and Google begin what will likely be a dance concluding with one or more of them being broken up (odds favor Google and Amazon being broken up, Facebook being sanctioned, and Apple being left to the States which have begun their actions).
Tighter competition generally shields the leading company from this kind of government response. Right now, NVIDIA doesn’t appear on any anti-trust action I’m aware of, but NVIDIA will need to be very careful they don’t abuse their market power to avoid being in that hot seat. NVIDIA has a decent reputation with its partners, and if they maintain that, they should be safe here, but it remains a risk.
When you are as far out ahead as NVIDIA does competitors, and particularly other countries will look to mine you for information illegally. This means everything from placing people in the company to get that information, appearing as customers rather than IP thieves to gain access to it that way.
This level of leadership in a technology area seen as a critical part of the next industrial revolution will be an extremely attractive lure that many may not be able to resist. NVIDIA needs to be able to share its technology with customers (it has sizeable open-source component) so that those customers can implement it in their products but, in so doing, will increase the likelihood of IP theft, meaning the firm will need to be extraordinarily vigilant.
When it comes to core AI technology, NVIDIA remains the company to beat and by an impressively significant margin. However, this is based on public information, and few are sharing where they are. This can lead to several problems for NVIDIA ranging from false confidence to intellectual property theft that NVIDIA should be able to deal with if they don’t take their eyes off the ball, and NVIDIA’s CEO is known for having eyes in the back of his head.
The biggest potential problem, though, is the abuse of their market power because that is something that tends to catch every company that becomes dominant up eventually and it is the most difficult to mitigate because it means putting in place oversight which managers universally find annoying.
Right now, NVIDIA stands alone, that will change, and whether NVIDIA remains out front or not, as this market matures, a lot will have to do with how the firm anticipates the related unique threats, including typical executive behavior.
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