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AnandTech

anandtech

The first part of the title of this story probably had you thinking this was a Pringles vs Doritos vs Lays brawl. Maybe one day, we shall see that clash. If you’re a bit familiar with the phone and laptop tech scene, then you know that for years Apple always has one battle or the other with some big tech brands. These battles are either held in a courtroom, subtly in ads or on social media. From when they battled with Samsung for years to their most recent battle with Facebook just last year. They even battled with the at some point. Does everybody actually hate Chris or do they just hate Apple? FBI Unsurprisingly, I bring you yet another battle. The M1 and Intel After 15 years, Apple decided to bring the bromance, between intel and its Macs, to an end. In 2020, Apple announced their yearly laptop releases: a MacBook Air, a MacBook Pro and a Mac Mini. As expected, they looked exactly like their predecessors. The only new thing was that they all had new chips. Apple created their own chips and decided to start using them in newer installments of their laptops and desktops. They had already been making their own phone chips for years and decided to do the same for their laptops. If you know Apple, you know that they have one of the best ecosystems of technology products in the world. They make life very easy for their users with seamless integrations that target overall convenience. Of course, this comes at a cost but nothing good comes cheap. Apple’s software is optimized to work with their hardware and this ensures efficiency. A trend that continued with their game-changing M1. Its efficiency boasted numbers never seen before. The M1 Macs have longer battery lives and better performances than their equivalent Intel predecessors. As a response, Intel launched its 12th-gen mobile processors earlier in 2022. This launch resulted in very powerful chips that aim to compete with Apple’s best. Even though Intel has been King of the hill for many years, the chip market is buzzing with competition. Without further ado, let’s jump into the numbers. Tests Tests were carried out by PCWorld, and Anandtech and generated results from the benchmark companies. These were the major laptop units used: MSI GE76 Raider (14-core Core i9-12900HK / RTX 3080 Ti Laptop @175TGP/ 32GB DDR5/4800) Apple Macbook Pro 16 (10-core M1 Max / 64GB LPDDR5/6400) Two other laptop units were used for better reference of performance results. Note that for test charts, longer bars mean better performance. all The first comparison is Cinebench R23. Results sourced from Anandtech and PCWorld were used. The benchmark is used to measure a CPU’s rendering performance. This is a stress test for 10 minutes. CPUs with more cores win. Spoiler Alert: Intel’s chip wins the first round by around 25% better performance. Since the Intel chip has more cores, it was bound to win this round. Cinebench R23 was also run using a single thread to compare CPU’s best cores. In this test, the new 12th-gen Core i9-12900HK also outperforms the M1 Max. A slightly older 11th-gen Core i9-11980HK also outperforms the M1 Max in this test, by a relatively small margin, The next test was Primate Lab’s Geekbench 5 benchmark. First up is the multi-core performance of all the laptops. For the MacBook Pro, the result was gotten from Geekbench’s database. This isn’t as reliable as one from a known outlet. Since results are self-reported, the circumstances under which they were run are unknown. Therefore, higher scores reported for the M1 Max were picked. Yet again, the 12th-gen Core i9-12900HK wins this round by a very little percentage. But no matter how small the margin is, there can only be one winner. There was also a report on the single-core performance from Geekbench. The core count doesn’t really matter because the result you see is the best performance of each CPU’s best cores. The M1 Max loses in this round again in what was a really close call. The other lower units tested didn’t also do too bad when matched against these super chips. Now onto GPU tests. The next test is called the Geekbench’s Compute performance benchmark. It evaluates GPU performance, simulating workloads like image processing, computer vision, and machine learning. A purple bar represents the integrated graphics and a green bar for the discrete graphics chips of the Core i9 and Ryzen laptops. The M1 Max is strictly an integrated design. Therefore, both bars are identical. The last test is focused on content creators that use the Adobe Premiere software. Results were compared and combined from PCWorld and PugetBench. Results were picked on the higher end of the scale for the MacBook Pro since it was from publicly sourced data. Conclusion Intel is a clear winner in this battle. While , they also never tell the full story. These numbers give a very good idea of how powerful the new Intel chip is, but not all metrics are measured. Real usage by real users gives the most accurate performance benchmarks. chips don’t lie In the end, people should pick computer hardware based on preference and functionality. If you are a software developer that loves gaming, picking a Windows laptop is a no-brainer since Macs aren’t for gaming. If you are a content creator that loves having a central ecosystem, you can go for the MacBooks with the M1 chips. Pick the hardware and OS that you need, rather than what the internet tells you. Cheers!

Clash of Chips: Apple's M1 Max vs. Intel's 12th Gen Core i9

Choque de chips: M1 Max de Apple vs. Core i9 de 12.ª generación de Intel

Clash of Chips : M1 Max d'Apple contre le Core i9 de 12e génération d'Intel

क्लैश ऑफ चिप्स: एप्पल का एम1 मैक्स बनाम इंटेल का 12वां जेनरेशन कोर आई9

Clash of Chips: Apple の M1 Max と Intel の第 12 世代 Core i9 の比較

Clash of Chips: M1 Max da Apple vs. Core i9 de 12ª geração da Intel

Clash of Chips: Apple M1 Max so với Core i9 thế hệ thứ 12 của Intel

芯片冲突：苹果的 M1 Max 与英特尔的第 12 代酷睿 i9

(For anyone following me on Medium, I appreciate the gesture, but my actual blog is . I’ll write a follow-up on the display issues themselves soon.) here It is impossible to explain anything non-trivial on , so I basically give up at this point. Here is more than 140/280 characters, because consumers deserve to know the basic picture: Twitter There is nothing inherently bad about OLED color accuracy, period. The Phil Schiller keynote slide on OLED displays was 100% nonsense. In Apple’s defense, they were really talking about the quality of their competitors’ displays in general. The slide made it look like these were inherent OLED issues, which was extremely misleading to consumers. Companies try to sell you a product, not teach and inform. OLED displays have been better than LCDs for the past few years. OLED has improved massively over many years but still has tons of issues. Both these statements are true. Samsung and Apple both always ship awesome displays. devices meanwhile have had both good and bad displays over the years. I would strongly recommend not reflexively being biased towards any brand or product, though, if you want to actually understand the . Google technology AnandTech has covered OLED displays in extreme depth over the years, so if you want to learn about OLED and all displays my highest recommendation would be to read their articles (can search for various previous device reviews). You can also follow @nexusCFX on Twitter. Android didn’t have color management until Oreo. Now it does. We’re good here. (There’s much more work still to be done for HDR support for Android P.) Because they have color management (and other factors), both the new Pixels target the Display P3 color space (which is currently correct for “wide color”), as many have stated. Google’s marketing even says this. How good the specific panel calibrations turn out to be is a separate question. Vlad Savov’s review unit for The Verge is clearly extremely green-shifted and looks awful. I won’t cover the work that needs to go into calibrating displays at the factory level here. not sRGB The 2 XL was always going to have a bad display. LG Display’s mobile OLED is many years behind Samsung Display’s and still suffers from a ton of issues. There’s not much Google can do here. And no, the answer actually isn’t “don’t source LGD OLED in the first place.” Google can’t work supply chain miracles. The 5.0” Pixel 2 could have a well-calibrated panel. We have no data, so I have no idea! There are a ton of potential issues with OLED in general, including off-axis color shifting, mura, moire patterns, uniformity more broadly, chromatic aberration, chromatic aliasing, and many more. These are all separate things, many of which clearly apply to the V30 and Pixel 2 XL’s displays. No one has publicly tested either Pixel’s display. Brandon Chester tested the original Pixel’s display, which unfortunately targeted the worthless NTSC color space and should be understood entirely in its own light (it was bad): . https://www.anandtech.com/show/10753/the-google-pixel-xl-review/3 Google isn’t stupid or unaware, and Romain Guy (the head of Graphics on the Android Team) in particular is phenomenal. Hardware, however, has often been a big struggle for Google due to insufficient engineering resources. Or investment and caring about hardware, if you don’t want to sugarcoat it. (Don’t even get me started on insufficient RF testing.) The Android Central text and video reviews were the most sensible ones I came across regarding display quality. Vlad, Dieter, and the rest of the Verge are good people, and I’m definitely not criticizing them :) Those folks helped me get into tech back in the Engadget days. You should never try to eyeball color accuracy or a calibration. Even professional display calibrators don’t trust their eyes: . https://techspecs.blog/blog/2017/7/21/why-you-shouldnt-use-someone-elses-tv-calibration-settings To assess color accuracy, you need actual data from credible testing. Unfortunately the necessary equipment and software cost thousands of dollars, even at entry level pricing. Panel variability is undoubtedly a part of the story. All silicon has variability. The iPhone X’s panel also doesn’t look so incredible at a distance. The color accuracy I’m sure will be excellent, but there’s a ton more that matters. It needs to actually be tested. I try to cover the little that I know at (and on , sigh). I promise I try not to write anything that I’m not pretty sure about. I also wrote about the rough details around the Pixel Visual Core a couple months ago if you’re into learning about that sort of thing. TechSpecs.blog Twitter And if anyone reasonably thinks, “this is just some random guy, why should I trust any of this?” I wouldn’t blame you, but I have talked with all the major display vendors over the years and have been given some behind the scenes explanations. If nothing else just believe AnandTech, whose credibility should speak for itself. AnandTech also isn’t dead, so stay tuned for some awesome stuff in the medium term :)

Debunking misinformation about the Pixel 2 XL’s display

Some things I learned while building a GPU rig for deep learning During this month’s , Apple said, paraphrasing, that they tried to put a in the 2013 Mac Pro, but it was too hot and caused the CPU to throttle. That was my interpretation at least. briefing on the Mac Pro TITAN X Apple has a tendency to put underpowered GPUs in their desktops, so it’s great to hear they’re seeking to improve this for the next Mac Pro. They’ve gotten plenty of that “pro” users want more powerful GPUs, such as NVIDIA’s or . feedback GTX 1080 1080 Ti by Pascal Eggert — [ ] 2017 Mac Pro concept Source Decades ago, CPUs added units (e.g. Intel’s ) for number crunching. Despite to improve use of the CPU, there’s no denying a recent away from the CPU to the GPU for this kind of computation. SIMD MMX techniques shift GPUs have become so powerful that we’re using them more, leading to a rise in general-purpose on GPUs. It’s a prominent time for GPUs now, AMD will be competing at the high-end again with their series, and NVIDIA is coming soon after that. computing Vega Volta “Most of the software out there that’s been written to target [certain kinds of high-end cinema production tasks] doesn’t know how to balance itself well across multiple GPUs but can scale across a single large GPU.”~ Craig Federighi It’s true don’t take much advantage of multiple GPUs, but the real point is that old weak GPUs won’t compensate for a new powerful one, and we shouldn’t beyond that context. It’s fairly likely that Apple will sell a Mac Pro configuration in 2019 containing two GPUs. some apps generalize So you need a fast computer A few years ago, if you were to buy a new Mac Pro, you could spend as much to upgrade the CPU ($3500) as it cost for the whole machine by itself ($3000). [ ] Source Earlier this month, Apple updated their Mac Pro configurations and pricing to something much more reasonable by today’s standards. A CPU upgrade from 6-core to 12-core is now merely : $2000 [ ] Source That cost matches the difference in Intel’s list price between the 6-core ( ) and 12-core ( ) processors, so Apple is simply passing along Intel’s suggested pricing. $580 $2600 Note that the clock speed of the 6-core unit is 30% faster than the 12-core one, so you’d be upgrading to slower cores. Apps that rely upon single-core performance will actually run slower on the more expensive CPU. Now consider that will buy you an NVIDIA . Last month this was the GPU available to the public. $700 GTX 1080 Ti most powerful For about the same cost as adding 6 CPU cores, you can have 3 of the most powerful consumer GPUs in the world. It’s a shame you won’t be able to plug all three of those monsters into the next Mac Pro. Assuming, that is, Apple designs it with similar expansion constraints as the cheese grater tower, which was the most expandable Mac Pro they’ve ever made. Two mid-range GPUs. Or a single high-end one. Apple supported dual GPUs before the 2013 trash can Mac Pro. In 2012, the cheese grater Mac Pro had a stock configuration that came with two AMD Radeon HD 5770 GPUs. A dual-GPU, modular Mac Pro (mid-2012) — Photo: / Tom Park CC BY-SA As with the GPUs in the subsequent 2013 Mac Pro, these were considered to be mid-range, not high-end. They are rated under 110-watts , so they draw less wattage and generate less heat than high-end GPUs (250 watts TDP is typical nowadays) of the sort that you’d want in a workstation-class tower. TDP “But you could replace those cards with more powerful ones,” one might say. While that’s possible, the box wasn’t designed to allow it. It has a decent power supply, . However, it provides only 150 watts to each video card, or a total of 300 watts. To support a pair of 250-watt GPUs, like the , you’d have to supply at least 200 watts more power somehow, possibly by wiring additional power cables from the drive bay ports or from the remaining two expansion slots. 980 watts GTX 1080 Ti Back in 2009–2012 when this Mac Pro model was being built, high-end GPUs tended to be 180–210 watts each, but even then you’d still be short at least 60 watts. In fact, Apple offered an alternative Mac Pro configuration with a single high-end AMD Radeon HD 5870, rated at - TDP. You couldn’t insert another one without additional custom wiring. The cheese grater case was simply not designed for a pair of high-end GPUs. 228 watts On the other hand, this Mac Pro had a replaceable CPU module that allowed upgrading the system from single to dual CPUs. That’s pretty cool — in most other computers, you’d have to replace the motherboard to upgrade to dual CPUs. But nowadays you’d want this kind of upgradeability with GPUs. OK, so let’s suppose Apple’s next Mac Pro is modular and expandable, like the cheese grater tower, and fitted with the latest tech: PCIe 4.0, Oculink-2, Thunderbolt 3, USB-C 3.1, M.2 NVMe SSDs, and LGA-2066 or possibly LGA-3647 sockets for high-end CPUs with 44 lanes of PCIe connectivity. That sounds promising, but how many GPUs will it support? Maybe two, if you fiddle with it? high-end Pfft, how many GPUs do you really need? This question reminds me of those people who were saying no one legitimately needs more than 16 GB RAM in a Macbook Pro. last year “Own the world’s greatest gaming computer and convince everyone it’s for your research” — http://imgur.com/wiLsGqA Three GPUs in a computer might seem ridiculous. Amongst the of Mac customers who buy a Mac Pro, an even smaller fraction would need more than two GPUs. single digit percentage There’d never be a controversy about Apple supporting only two GPUs. But if one came up, a person might claim that no one legitimately needs more than two GPUs. Then a person would be wrong. Two weeks, two weeks, two weeks If you try to make an AI program to recognize 1000 types of objects in a photo, one of the things you’d find out is that even with multiple GPUs it can take weeks or months to train a neural net. We can train a model from scratch to its best performance on a desktop with 8 NVIDIA Tesla K40s in about 2 weeks.~ Jon Shlens, Google Research The common advice to avoid this delay is to adapt one that’s already been trained, using a technique called “ ”. But depending on what you want to do, you can’t always be using someone else’s pre-trained neural net — at some point you’re stuck in a process where each iteration could take weeks. If at that point you’re using only one GPU, adding a couple more would reduce the turnaround time significantly. transfer learning Suddenly synthesized A common problem with neural nets created by “supervised training” is they need a huge amount of training data or else slight variations in input will fool them. That is, suppose you train a neural net to recognize cats, but your training data consists of photos where all the cats are sitting upright. It might not recognize a cat that’s upside down. Your program will handle these kinds of differences better if you augment the training set by adding rotated and resized copies of the originals. In a notable example, Baidu Research made a breakthrough in speech recognition, aided by layering noise over their initial data set. Baidu gathered about 7,000 hours of data on people speaking conversationally, and then synthesized a total of roughly 100,000 hours by fusing those files with files containing background noise.~ Derrick Harris, GigaOm But then they had 14 times more data, which takes that much longer to process. A few years ago Baidu . More recently they reported working with as many as or GPUs. used 8 GPUs 40 128 Now you have two problems Recently some of the coolest results in AI are based on a technique where two neural nets compete against each other (“ ”) to improve their ability to create and recognize types of data. generative adversarial networks With a larger model and dataset, Ian [Goodfellow] needed to parallelize the model across multiple GPUs. Each job would push multiple machines to 90% CPU and GPU utilization, but even then the model took many days to train.~ OpenAI Blog That means you’re training two neural nets, not just one. Again, you’ll want as much computing power as you can get. Would you pay extra for expansion slots? When I started doing deep learning work, I used GPU spot instances on Amazon cloud. After running up a small bill, I began looking into external GPU boxes, but ended up assembling a PC. The GPUs on AWS are now rather slow (one GTX 1080 is four times faster than a AWS GPU) and prices have shot up dramatically in the last months. It now again seems much more sensible to buy your own GPU.~ Tim Dettmers I bought just one GPU. But knowing that I might need to add more, I made sure that the PC would be able to take up to four. It’d been a long time since I’d built a computer from components, and way back then I wasn’t paying attention to how many GPUs I could put in it. To my surprise, many computers cannot support two GPUs at full bandwidth, and most cannot support more than two. There are only a few expensive motherboards that can support 4 GPUs simultaneously with x16 lanes of PCIe 3.0 connectivity. The ability to add 3 more GPUs cost me about $600. That’s about one-third of what the base system (w/o GPUs) would cost if built with standard components. This amount represents the higher prices for a quad-GPU capable motherboard, a big 1500-watt power supply, and a CPU with 40 PCI lanes (as opposed to 28 lanes). I literally paid extra for expandability itself. Would Apple sell additional expansion as an option? The Mac Pro is positioned as Apple’s most powerful computer, but computing power is coming in various forms. High-speed expansion slots provide the ability to upgrade computing power in whatever form it takes in the future. We’re not just talking about GPUs here — it might be , or like Google’s . Or . FPGAs ASICs TPU fast storage Computer manufacturers generally do not sell a single line of desktop computers with different cases. For example, you don’t usually see something like this: by Scott Richardson —[ ] 2013 Mac Pro concept Source Instead, the models of a computer line are positioned according to CPU speed, storage, and/or screen size. So this is what’s typical: https://www.apple.com/mac-pro/specs/ But doesn’t it make sense to sell optional expandability? It has value. You can put a price on it. C’mon you have to admit it’d be pretty cool 😎 I know what you’re thinking: “There’s no way Apple would do this. It’s not worthwhile because there aren’t enough customers for the bigger Mac Pro.” You’re probably right. And besides, it’ll have Thunderbolt-3, and maybe Oculink-2 which is even faster, so people can connect GPUs if they need them… you know, like this: external Photo: Peter Wiggins — [ ] Source Anyway, I’m looking forward to seeing how Apple rethinks the Mac Pro. When we hit three GPUs, we are technically in a niche category… From talks with ASUS, despite the fact that a product may be geared towards a niche market, that product may sell well to the standard market if it is perceived to be good.~ (review of multi-GPU boards) Ian Cutress, AnandTech Q&A Asking the tough questions. What’s the big deal about multiple GPUs — weren’t bitcoin miners putting 6 or 8 GPUs on a PC in a ? milk crate Yes, but cryptocurrency algorithms can run on a GPU without a lot of data transfer, so miners could use PCI riser cables or a PCI splitter, and connect each GPU using just one PCI lane. That means they didn’t need a 40-lane CPU and a quad-x16 slot motherboard. In bitcoin mining, GPUs were overtaken by ASICs. Won’t that happen in AI too? Probably, at least and are working on that. In the meantime, GPUs have versatility that make them useful for the future. Nervana Groq foreseeable ASICs have lower power requirements than GPUs, so wouldn’t a big power supply be unnecessary for multiple ASICs? Maybe, but then you might just get more ASICs on each expansion card. You mentioned FPGAs and ASICs, but what about quantum processors? Oh yeah, those too I guess. Why do you need 16 lanes per GPU? Games don’t show any difference between GPUs running on x8 vs x16. It’s true that games show no significant difference, but that’s probably because they’re tuned to run well on GPUs at x8. Games don’t saturate a x16 PCIe 3.0 connection, but other apps like deep learning programs can. How does a CPU with only 40 PCI lanes connect to 4 GPUs that each use 16 lanes? Right, 4×16 = 64, which is more than 40. The motherboard has two PCIe switches which each can multiplex 16 lanes of signal from the CPU to 32 lanes for two slots. So the 4 slots use only 32 lanes from the CPU. a similar kind of PCIe switch for the Thunderbolt 2 controllers in the 2013 Mac Pro. Apple used Don’t those PCI switches introduce a lot of latency? Some people say the latency is so bad that it’s better to just use 8 lanes, but that’s a . Apparently this idea spread due to game testing that showed slightly higher frame rates on x8 GPUs than on switched x16 GPUs. But games are not good for this kind of benchmark because they don’t exceed x8 bandwidth — you can get similar results on a unswitched x16 slot. myth I haven’t seen any good tests, but an NVIDIA showed very little latency or loss in bandwidth across a PLX (Avago/Broadcom) switch. benchmark Show us your rig. Pics or it didn’t happen. Here it is next to the cheese grater: An open case rig next to a Mac Pro 5,1 — Photo: / Tom Park CC BY-SA What the… ugly. Why no case? OK, so I have to vent a little about motherboard and case design. Cool desktop computer designs are totally thwarted by the way uATX, mITX, and ATX boards are standardized. This sector has so much room for innovation with non-standard motherboards and backplanes. A lot of people are calling for Apple to just put the next Mac Pro in a big box case, but I think it’d be a shame if that’s exactly what Apple does. They went to extremes with the 2013 Mac Pro but reverting to a standard tower box isn’t so appealing either. I wanted a smallish form factor but the motherboard is so big (extended ATX) that it would have to go in a fairly large case, and I didn’t like anything I saw. So I experimented with MakerBeam rails instead of imitating with a Carbide Air 540 case. It ended up being taller than I intended, but slim in other dimensions. NVIDIA’s DevBox A single-fan liquid cooler has been completely adequate for the CPU. The GPU is connected with a x16 riser cable and can slide all the way over the CPU, since the CPU doesn’t have a huge heat sink on top of it. That means multiple GPUs can be spaced apart with wide air gaps. It’s surprisingly quiet with two 140mm fans, even under sustained heavy load. What did make a huge amount of noise was a 5TB hard drive that was hammering away while feeding images to a convnet. After a couple annoying days of that, I switched to a SSD. It has no drive bays — there’s a M.2 drive and additional SSDs can be velcroed on a side rail.

The Mac Pro: A Case for Expansion

Layman’s Tech: a guide to new gadgets, products, and fun—for those who don’t have a degree in computer science. These days, it seems as though VR headsets are raining from the sky at the rate of a biblical plague—minus Apple’s very notable absence in the space, of course. So, which headset do you choose? Obviously, each product’s website will give you their own sales pitch, describe their product with top marks, and practically guarantee it is the best thing since the Amazon-type site reviews are slightly more reliable, but only for a single product. Rapid Ramen Cooker. Below, I’ll go compare three different headsets, each drastically different in price. To keep things equal between the sets, we won’t delve into gaming in VR. As you read below, imagine your only goal is to watch a video on the device. Maybe that is your only goal (I don’t know you that well). Suffice it to say, such a simple operation is very different among all of these. VR One Plus Up first, the VR One Plus by Zeiss. This headset is not the cheapest of the three, per se, but it has the ability to be the cheapest . , it is a common item at many big box retailers. If you’re in need of a go-to for a fun weekend with the family, you’re nearly guaranteed to find this option locally. operating package Coming in at just $129 At first glance, it’s not the most chic rig on the market. The white shell helps it stand out from many of the completely-black products on shelves, but upon touching it, it’s easy to tell this white plastic will yellow quickly. Look at all that cushiony goodness! The headset is simply an apparatus to hold a phone, similar in function as . In comparison, though, this has comfortable head straps and a face cushion, so extended use is comfortable and leaves your hands free to do the dishes or walk the dog. Additionally, the head straps adjust easily, so switching from one user to another is quick and nearly painless so long as your three-year-old niece, Sasha, doesn’t find great humor in placing your hair on the velcro. Google Cardboard To use the set, simply grab your phone (or any smartphone) and find a 360 video. Making sure the video is set for VR (YouTube has a small icon on the bottom right looking like Google Cardboard), stick your phone into the included tray. The tray seems to adjust for just about all smartphone sizes ( ), and a smartly placed pad helps keep everything secure. Hit play, slide the tray back on into the headset, and start viewing. disclaimer: I didn’t buy all smartphones to try this YouTube makes it easy to view 360 videos on your phone or in a VR headset. The tray is easy to insert and remove when empty. With the added weight of a phone, it becomes a bit too easy to remove, though. Tilting your head drastically to one side, or even just holding the headset off-kilter can cause the tray to shift. It is easily re-situated but can be a bit of a nuisance when trying to share an active video with another viewer. Aside from the tray, no additional buttons or knobs adorn this set. From having used other sets, I know this means there is no adjusting the lenses. As a person who only uses cheater glasses when needed, this is not a downfall for me — adjusting the lenses on other headsets doesn’t typically provide a notable difference. I can’t accurately say whether this makes a huge difference for those who wear glasses regularly, so I won’t try. I have a minor addiction to glasses. One of the major drawbacks accompanying this type of headset is the requirement to hit play in advance. Inevitably, you will miss the beginning moments of the video. Plus, once the videos are put into 360 mode, the “play” icon is small and more challenging to hit on the first try. This is a minor inconvenience when it comes to affordable and accessible VR, though. Finally, as with Google Cardboard, this headset only allows you to view photos and videos. I’ve heard this put as being restricted to three degrees of freedom (3DOF) when VR “should allow” for six degrees of freedom (6DOF). In essence, you’re not really able to explore areas or do any sort of gaming, but if you’re just looking to Snapchat your Nanna experiencing the world’s steepest roller coaster ride after Sunday brunch, this might be the perfect option for you. Graph coloring courtesy of the 1990s. Let’s take a short moment to describe 3DOF and 6DOF. Imagine for a moment you are on one of those intimidating X, Y, Z axises relentlessly drilled into your head in Freshman Geometry. On that graph, you have three lines. One goes up and down, another goes from left to right, and another goes front to back. If you were to sit stationary where the lines converge, viewing your surroundings from that spot, you get three degrees of freedom. Six degrees of freedom, however, allows you to those spaces. Instead of looking up or down, left or right, backward or forward, you can physically move around on those axises. This is a common function in many VR programs and VR gaming. explore Gear VR Next up is the Gear VR (2016) by Oculus. To be clear, this is not the most recent model, but it is only a handful of months old and functions in mainly the same ways as the newest version. , this is the cheapest headset I’m reviewing today. This headset comes with a catch, though: you have to use one of their approved Samsung phones. In the same way that I am not a computer developer, I am equally inept at reading cell phone contracts. So, you can figure out for yourself, should you so choose, how much a Samsung phone would cost in your world. A safe range for an unlocked version, however, would be around $700-$900. At an original purchase price of just $99 Together, that makes this headset a nearly $1000 package. Photo courtesy of . patentlyapple.com/ Thankfully, Samsung seems to have gotten that exploding phone thing under control. I don’t know about you, but the last thing I thought about during the period of time when their phones were so dangerous they were banned on airplanes was taking one and strapping it to my face. Today’s version of Russian roulette? At first glance, color aside, the Gear VR and the VR One Plus look very similar. The Gear VR is a bit wider and boxier, and close inspection shows knobs and buttons. It has the same cushioned headrest, and the head straps are virtually identical. Looking at the application for attaching the phone, however, proves to be more complicated. One side allows you to move a bracket to fit different Samsung phones, while the other attaches to the charger port on the phone you’ve chosen to use. Adjusting for the size is not as easy or graceful as I’m sure Samsung would have hoped. I would guess that after repeated use, this becomes easier, but I also assume I’ll be using the same phone most of the time, so adjustments won’t be terribly necessary. The port side seems flimsy and scary. You have to flip it up, attach your phone, and then slam it back down — all while the only thing holding on to your phone is the port. It wobbles a bit, and I would suggest doing this while standing over a very close surface, such as a table. I don’t claim to be the most coordinated person on earth (I’ll never be going to the knife-juggling olympics), but when setting up VR requires this much concentrated coordination, I’m already a bit let down. Additionally, after repeated use, the port becomes more unstable. The setup becomes less reliable, with videos either cutting out midstream or not getting the signal altogether. Using the Gear VR is much more interactive than the VR One Plus, though. Once you’ve unlocked your phone (a creepy mechanical woman yells at you if you don’t) and hooked it up to your set, the Oculus App (which you must download) triggers. With the headset on, all of your controls are through the headset. Suddenly, the buttons and knobs become functional, and the combination of your eyes and a touchpad become your mouse. As a side note: this is the only VR headset I’ve used where the focus dial actually shows me an obvious difference between levels. It’s easy and lovely. There are some additional steps needed, now. You have to create accounts, and set up you virtual areas (a living room in which I’d like to spend all of my time) in the same way you’d initially set up your computer’s desktop. Most of these steps are fairly simple for anyone who’s done much on a smartphone. There’s added time here, so it’s not quite as immediately gratifying as the VR One Plus, but the benefits of future organization for finding your videos/pictures are obvious. Oculus’s home screen: a beautiful living space. All it needs is a sweet-looking cat to wander toward me, rub up on my leg asking for pets followed by hissing and clawing for not doing it “just right.” Photo courtesy of VRHeads.com. A downside? Well, it’s a headset (and app) run by Oculus. In the VR space, there are two main players right now: Facebook and Google. Oculus partners with Facebook, so they, very candidly and effectively, take the Google-owned YouTube off the list of available sites. There are hacks to get around this — none of which I will list here — but they are rather tedious. Even more importantly, the point of this blog is to let you know what you can or can’t do on a headset. Oculus you to view YouTube videos on their products, so they make it exceptionally difficult. does not want YouTube aside, there is still plenty to see on the Gear VR. You can download game apps, watch videos on their servers, or load your own onto your phone. There are fairly simple instructions included with the headset about how you would do this, but make sure to follow them precisely. You are not able to explore your phone’s photos on this set, so you must create specific folders in which to place the ones you want to view in VR. I would love to see this go to a cloud-based service, since videos and photos take up quite a bit of space on a phone. Keeping a large digital library on such a memory-limited device will only work well for a small bit of time. Photo courtesy of . anandtech.com Oculus Rift Onto today’s heavy-hitter: the Oculus Rift (by, you guessed it, Oculus) I will start by saying this particular headset, given its ability in the VR space, warrants its own review. I will also say I’d have preferred for number three on this list to have been a Vive. Having two Oculus products isn’t quite as diverse as I desired, but the capabilities between the these two should be sufficient for today’s goals. The Oculus Rift is quite the setup. Be prepared for chord tangles and you may want to dedicate a single outlet to this contraption. The headset itself . This gets you a stunningly-packaged VR set. It comes complete with a controller (in my case, it’s an Xbox), a remote, a tracker/sensor, a headset, and a cord long enough to span the entire Autobahn. Together, these items get you exactly . cost $599.99 at the time of purchase nowhere Sadly, this is the one instance where “42” is not the answer. To actually use the headset and accessories, you’ll need a computer. For gaming or extended use, a high-powered computer is preferable. In all honesty, Oculus never claimed this was a self-contained system. They even go so far as to provide computer recommendations for optimal use of their setups. You’ll notice the one I’m showing uses a laptop for portability, but additional accessories (such as a cooling tilt table) were needed for maximum efficiency. We can get into all of that at a later date. For now, let’s look at the basic setup and usability of the overall contraption for the purposes of watching a video. While the previous Oculus rig already had me set up profiles and the such, more is now needed on the Rift. The initial setup (figuring out where cords go, buying extenders so they actually hit their ports, and additional profile administration) took hours. This Oculus works in a similar fashion to the previous, though. Once hooked up correctly, simply placing the set on my head triggers the program to open. Inside my digital living room, I have even more options than I was offered on my Samsung rig ( ). I am also more apt to download apps and programs, as I am less fearful of running out of storage space. Downloading takes quite a bit of time; prep for that. The updates to these are frequent and incessant. although, there’s still no cranky cat As with the previous Oculus set, I am unable to view YouTube videos. Again, I have options to get around this, but they are even more tedious, time consuming, and costly on the Rift. With Gear VR, I was able to put my own videos into a folder for viewing. This headset claims the same is possible (in a folder, so be mindful of the directions), but I have yet to get that to work. While the online directions on Oculus’s site were clear and simple (only four steps, I believe), no videos are watchable via their programs just yet. different After countless hours I was at a loss; I contacted Oculus directly. Their response time was very prompt and quite courteous. However, it’s the same game as with most tech support: write the same problem out three times in three different ways to three different people, be directed to the same four steps over and over, and the resolution has yet to come. I will say, they seemed very dedicated to helping me solve the issue. I’ve no doubt this is an issue they want solved, and they are actively working at finding a solution—after all, they are invested in the future of this product—but for the time being, my videos were held hostage. (and actually pulling in someone going to school for computer science — thanks, Jaron!) Perhaps at a later date, I will go into how I got everything working (along with the help of my computer-science pal). It’s a complicated path, and it involved purchasing three additional apps which all need to work together, update together, and connect to the internet for viewing a video on a hard drive. I hardly have the patience to write the steps now, and I would venture that if you’re still reading to this point, you could use a break as well. Come on, you deserve it! To Recap It’s clear the manufacturers of each set has a different clientele in mind. Comparing apples to clown-costumed pigeons hardly seems fair, but knowing which type of rig is best for you is important. If you just want to view 360 in 3DOF quickly, cheaply, and portably, this is a great option. VR One Plus: great for the plop and go. It’s not plop and go, but it can’t give you 6DOF, either. It is arguably more expensive than the VR One Plus and requires much more time for setup. A decent option for someone already owning an un-exploded Samsung phone, but not a go-to for the mass population. Gear VR: a niche Samsung market. Allowing for more functions (such as gaming), this set gives you 6DOF using the right programs. As is true for everything, more options gives way to more problematic opportunities. I won’t yet say watching videos isn’t possible, as I know a fix will be upon us soon, but this type of a setup is more of an investment for those who are truly into the VR space. Oculus Rift: for the sit and stay. Happy Virtual Reality-ing! We are all very used to the crispness of today’s TVs, cameras and computer monitors. VR is not yet at the same level. Each headset had slightly varying degrees of clarity, but the biggest game-changer in resolution will come from 360 camera evolution. For that reason, the clarity of the actual viewers seemed unnecessary. Stay tuned for 360 camera reviews.

Three VR Headsets Walk into an Apple Store…

RF Tunable Filters Market: Introduction Transparency Market Research delivers key insights on the global RF tunable . In terms of revenue, the global RF tunable filters market is estimated to expand at a CAGR of 8.3% during the forecast period, owing to numerous factors, regarding which TMR offers thorough insights and forecasts in its report on the global RF tunable filters market filters market The global RF tunable filters market is broadly affected by several factors, including rising adoption of MEMS-based tunable RF filters. RF Tunable Filters Market: Dynamics RF tunable filters are electronic components used to allow or prevent selected signals or frequencies in order to eliminate noise or pass-through of unwanted signals. The radio frequency spectrum includes the set of frequencies of the electromagnetic framework, ranging from 30 Hz to 300 GHz. It is divided into several ranges, or bands, and given labels, such as low frequency (LF), medium frequency (MF), and high frequency (HF), for easier identification. The rapid expansion of 5G networks fuels the demand for new and higher frequency bands with high performance standards for RF filters. The proliferation of 4G LTE networks, increased adoption of new 5G networks, and Wi-Fi have raised the usage of RF bands that smartphones and other mobile devices support. The telecommunication industry is developing new resonating structures to filter unnecessary interference signals at these high frequencies. In September 2021, Resonant developed new XBAR resonator technology for the optimization of RF filters used in 5G and Wi-Fi networks. Therefore, an increase in the implementation of 5G across the world and bandwidth demands of 5G networks are anticipated to offer lucrative opportunities for new generation of RF filters, which, in turn, needs new generation of tunable RF filters delivering throughput and providing for signal coexistence. In June 2019, China granted commercial licenses to four state-owned telecom giants namely, China Telecom, China Mobile, China Unicom, and China Radio, and Television to start rolling out 5G services. The government has aimed to make Beijing a leading global city in setting up superfast wireless networks amid tensions with the U.S. over technology and trade. Thus, rising implementation of 5G across the world is expected to fuel the RF tunable filters market. RF Tunable Filters Market: Prominent Regions The RF tunable filters market in North America is expected to expand during the forecast period, owing to the presence of key market players, technological advancements, and expansion of the aerospace and defense, and telecommunication sectors in the region. North America has the presence of robust expanding economies, including the U.S., Canada, and Mexico. Industrial expansion coupled with the presence of a well-established supply chain network catering to a wide range of industries, including aerospace, healthcare, defense, telecommunication, energy & power, and mining is expected to propel the demand for RF tunable filters semiconductor substrates; consequently, driving the global RF tunable filters market. The U.S. accounted for a prominent share, in terms of value, among all countries. The RF tunable filters market in North America is projected to expand further due to a significant rise in the demand from aerospace and defense industry. The North America market is estimated to reach a value of US$ 77.28 Mn by 2031. The RF tunable filters market in Europe is likely to expand at a notable CAGR of 8.5% during the forecast period, owing to the presence of enough number of players manufacturing RF tunable filters in the region. RF Tunable Filters Market: Key Players Key players operating in the global RF tunable filters market are K&L Microwave, Analog Devices, Inc., Benchmark Lark Technology, Pasternack, Smiths Interconnect, Anatech Electronics, Inc., EXFO Inc., Netcom, Inc., Lorch Microwave, Pole/Zero Corporation, and MtronPTI. TMR Latest News Publication: ·  Semiconductor IP Market: https://www.prnewswire.co.uk/news-releases/growing-digitalization-trend-in-many-industries-drives-striking-demand-avenues-in-semiconductor-ip-market-tmr-800607263.html · Fiber Optic Connectors Market: https://www.prnewswire.com/news-releases/pandemic-trends-to-help-fiber-optic-connectors-market-develop-at-8-1-cagr-over-forecast-period-of-2019-to-2027--notes-tmr-301172733.html About Us Transparency Market Research is a global market intelligence company, providing global business information reports and services. Our exclusive blend of quantitative forecasting and trends analysis provides forward-looking insight for thousands of decision makers. Our experienced team of Analysts, Researchers, and Consultants, use proprietary data sources and various tools and techniques to gather, and analyze information. Our data repository is continuously updated and revised by a team of research experts, so that it always reflects the latest trends and information. With a broad research and analysis capability, Transparency Market Research employs rigorous primary and secondary research techniques in developing distinctive data sets and research material for business reports.

Filters Market Projected To Garner Significant Revenues By 2031

Dr. Sabine Hossenfelder’s is titled ‘ ’. latest YouTube video It looks like AI will kill Quantum Computing I would like to share why this shall not happen before this jab at quantum computers turns cold. Quantum Computers Are of Great Research Interest If you went away from the video with an earnest belief that AI shall indeed kill quantum computers by drying up its research funding, then you might as well believe that AI will kill particle physics, cosmology, and quantum gravity. And where the hell is the Higgs Boson hiding if it holds more mass-energy than a hydrogen atom? Just saying. Continuous progress in the theoretical and experimental realization of better quantum computers is of great interest to human beings because it is a real way to uncover computational truths about the universe. We are curious about building big, powerful quantum computers like we are curious about what happens inside a black hole. Shall a big powerful quantum computer hack RSA and uncover all those hashed-up secrets (about aliens)? I want to find out. Does a black hole teleport us into another Universe? Dr. Sabine is interested in this one. As AI makes big tech founders billions and soon to be trillions of dollars once we start putting servers on the moon, a lot of that newfound funding will go towards, take a guess, research in quantum computing. Computing Is Not Always About Speed The Graph We are always comparing the computational speed of quantum computers with that of classical computers in the graph below. The graph above starts with the line for quantum computing above that of classical computing. This means that classical computers are more efficient and take less time to do operations. Later on, there is a cross-over point, and classical computers take way more time to do the operations compared to a quantum computer. That cross-over point is when a quantum computer of modest size and complexity hacks classical encryption algorithms, simulation problems, and that no classical computers can hack. traveling problems Dr. Sabine argues that AI is shifting the lines and the cross-over point into the very far future, making Meta senior fellow and former tech chief Mike Schroepfer exactly right when he says “quantum computing being irrelevant to Meta right now”, quite prescient. …”(quantum machines) may come at some point, but it’s got such a long time horizon that it’s irrelevant to what we’re doing.” source But computing is not always about solving problems quickly. Modelling Computing is also about modeling problems. While the latest QC - the - is not gargantuan enough for the computational problems that most people are paying for, the fact that you would need a supercomputing complex to model what it can model should be impressive enough. 433 qubit IBM Osprey Know what, we should do it. Let us model something impressive in Osprey and also try to model it on See which one uses less electricity. This modeling contest can be appreciated as high art and designed to get people entertained. Where there is entertainment, people are willing to pay for it. Frontier. On a more practical note, quantum sensors built at the measurement side of quantum computers are a peak into the universe that classical computational sensors have no hope of seeing. Of note are LIGO and Atomic clocks. The latter can see and count atomic zeptoseconds using minimum energy periodically cycled by continuously exciting an atom. Telling time very accurately helps us keep an accurate, albeit . clunky calendar The former can see gravitational waves using a variation of the Mach-Zehnder interferometer. In the quantum computing world, this is just a singular CNOT gate. So, if one CNOT gate can see gravitational waves, wonder what our elaborate algorithms can see. We need to find out. The measurement-computing use cases for quantum computing shall only get more impressive. I hope to one day measure the Hamiltonian of the . smallest Bitcoin miner possible AI Might Love Quantum Computing We need to realize that AI might love quantum computing, because AI loves learning. AI might be pushing the boundaries of classical computers to make them develop heuristic powers that people who train AI models also marvel over. But no matter how hard you push a car, it will never be a boat. While AI is still poor at explaining quantum mechanics compared to most human physicists, that might change once we keep pumping AI with quantum computing data. Machine Learning of Quantum (MLQ, not which is ) technology should be of interest to Meta because the road to developing better quantum computers will also develop better nanomaterials relevant to the classical computing world. QML Quantum Machine Learning The quantum computing world, like the classical computing world, is now parked at the nanoscale. Being neighbors, they could benefit from each other. They will. P.S. >> Quantum Computers also have their finger on improving battery technology because an entanglement of atoms packs more energy than if you did not have an entanglement. Admit it; these quantum computers are interesting.

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