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Take the example of Elon’s Musk’s infamous support for Dogecoin. The latest tweet recovered the 10% drop it witnessed a day earlier. One tweet can be the difference between the life and death of the next breakthrough in the digital asset space. Such is the power of influencers in crypto.
Coinfluence: The Crypto Influencer Platform of the Future
Coinfluence solves the crypto influencer marketing problem by connecting upcoming projects with a wealth of high-level influencers. The outcome is an environment where
projects get access to high-quality social media influencers that can attract the right crowd and increase the chances of a successful launch while the influencers get to be a part of the next breakthrough in crypto, creating fantastic win-win situations. And of course, a good project doesn’t necessarily translate into a successful one if it remains under the radar. Access to a wide range of influencers means that it will get the right exposure, putting it on the map where it truly belongs.
Coinfluence achieves this with a tight-knit set of strategies. First, any project that wishes to be listed must go through a stringent quality check that is based on a multitude of factors, allowing only thoroughly vetted projects to be listed. This creates a cleaner and better option for investors, whilst protecting the market from scams, rug pulls, and bad actors.
At the centre of this whole ecosystem is the CFLU token, designed to assist projects and influencers to achieve mutually beneficial outcomes. Approved projects get to hold their token sales through the launchpad, where the community can acquire their tokens using CFLU. Each transaction gets taxed, with the amount being distributed for liquidity, staking rewards, and marketing. At the same time, the deflationary token model should push the CFLU price upwards.
CFLU Token Sale Event
Driving the economics behind Confluence’s ecosystem is the Binance Smart Chain-based BEP-20 compliant CFLU token. Based on the principles of deflation, there are a total of 1 billion CFLU, of which 650 million are already available in the currently ongoing token sale. The event is phase-based, with each of the 100 successful phases making the CFLU progressively more expensive (currently phase 1 has a price of 0.0056 USD per 1 CFLU).
Out of the 650 million CFLU, 100 million have been set aside for financing the platform developers. To give confidence to projects, influencers, and users of CFLU, a vesting schedule will allow the team access to 20% of the funds, with the rest being released periodically. This ensures that rugpulls are guaranteed against.
An innovative tax system is also a unique approach, by which 10% of all transactions are deducted, with 4% going to the liquidity pools, 4% to token holders, and 2% for marketing and expansion. Along with this, every 10th transaction in the first 1000 transactions will receive 5000 bonus tokens as a reward. Visit the Coinfluence ICO platform to get your CFLU tokens today.
The Present and the Future
The Coinfluence concept materialized at the start of 2023. Alongside this, the Coinfluence team has achieved onboarding a large number of influencers and it has set a target of 100,000 top influencers under its Enrolment Program.
Coinfluence is also building towards global collaborations and getting CFLU listed on major exchanges, to provide increased liquidity and access for the everyday user to the CFLU ecosystem. Confluence is also looking to list CFLU on major coin monitoring platforms such as CoinMarketCap and CoinGecko, plus portfolio tracker Blockfolio, to raise awareness and increase information transparency.
Further down the road, Coinfluence will be launching its mobile app for access on the go. Confluence will be also roll out their own launchpad, giving projects a one-stop solution to top influencers and the many intricacies involved in project setup and launch, all at the same time. Finally, Coinfluence will create its own news platform, the Coinfluence News Network to inform its users and the public on the latest happenings in the industry.
Visit the Coinfluence ICO platform to get your CFLU tokens today.
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Decoding The Next Generation Of Ai
Robotics brings together a wide range of different machines including Pepper partnering with soft-bank; the Boston Dynamics humanoid robot Atlas, which can do backflips in movies and television and a plethora of humanoids and Bots that leave the human mind with awe and inspiration to achieve new tech heights. Much that the technology that powers robotics continues to achieve new pinnacle; people not familiar with the developments tend to hold polarized views, ranging from unrealistically high expectations of robots with human-level intelligence, or an underestimation of the potential of new research and technologies. Over the past years, questions have been asked about what is actually going on in deep reinforcement learning and robotics industry. How are AI-enabled robots different from traditional ones and their underlying potential to revolutionize various industries, what is the new excitement the robotics industry holds for the future. These questions point towards the challenging world of robotics and how difficult it can go to understand the current technological progress and industry landscape, to enable tech giants and newbies alike to make predictions for the future.
The Uniqueness Behind the AI powered RobotsSo what is about the robot evolution from the automation to autonomy? What started off as a quest to make routine work easy through automation has come a long way towards full robot autonomy? AI brings a game changer approach to robotics by enabling a move away from automation to true self-directed autonomy. When the robot needs to handle several tasks, or respond to humans or changes in the environment, it essentially needs certain levels of autonomy. The path from autonomy has been an uphill but a truly worthwhile change. According to a source, the evolution of robots can be explained by burrowing case studies from the autonomous car space. For an easy explanation of the process underlined below, robots are defined as the programmable machines capable of carrying out complex actions automatically. • Level 0 stage is also called as the No automation stage where people operate machines, there is no automation without any robotic involvement. • Level 1 stage is the driver assistance level, where a single function or task is automated, but the robot does not necessarily use information about the environment. Traditionally, robots are deployed in automotive or manufacturing industries programmed to repeatedly perform specific tasks with a high precision and speed. • Level 2 stands for partial automation where a machine assists with certain functions, using sensory input from the environment to automate some operational decisions. Examples include identifying and handling different objects with a robotic vision sensor. In this stage, robots lack the ability to deal with surprises, new objects or changes. • Level 3 is the Conditional autonomy where the machine controls the entire environment monitoring, but still requires a human’s intervention and attention for unpredictable events. • Level 4 is the high autonomy stage where the machine is fully autonomous in certain situations or defined areas. • Level 5 is the complete autonomy level powering the machine with full automation in all situations.
The Current Stage of AutomationToday, a majority of robots deployed in factories are non-feedback controlled, or open-looped implying that their actions are independent from sensor feedback as that happens in level 1 stage as discussed above. Few robots in the business act and take commands based on sensor feedback as that happens in Level 2. A collaborative robot, or co-bot, is designed to be more versatile empowered to work with humans; however, the trade-off is less powerful and happens at lower speeds, especially when compared to industrial robots. Though a co-bot is relatively easier to program, it is not necessarily autonomous to handle. There is often a need of human workers to handhold a co-bot every whenever there is any change in the environment or the task. Pilot projects integrated with AI-enabled robots, have started to become a regular feature incorporating a Level 3 or 4 autonomy, like warehouse piece-picking. Traditional computer vision cannot handle a wide variety of objects like that in e-commerce because each robot needs to be programmed beforehand and each item needs to be registered. However reinforcement learning and deep learning has enabled robots to learn to handle different objects with minimum human assistance. In the times to come, there might be some goods that robots have never encountered before which would need a support system and a demonstration from human workers bringing the level 3 of automation. In the times to come, improvements will be seen into algorithms to get closer to full autonomy as the robots collect more data and improve through trial and error in Level 4. Taking a clue from the autonomous car industry, robotics startups are additionally taking different approaches to autonomy for their robots. Some aspects believe in a collaborative future between robots and humans, and focus on Level 3 mastery. While in a fully autonomous future, skipping Level 3 and focusing on Level 4, and eventually on Level 5 will be difficult to assess the actual level of autonomy.
The Age of AI-Enabled Robots in IndustriesTaking the brighter side, robots are being used in a lot more use cases and industries than ever before. AI-enabled robots are running warehouses, in a semi-controlled environment, picking up critical pieces that are fault-tolerant tasks. On the other hand, autonomous home or surgical robots will be a reality of the future, as there are uncertainties in the operating environment, where some tasks are not recoverable. With the change in time, the human eyes will see more AI-enabled robots being used across industries and scenarios as reliability and technology precision improves. The world has seen only about 3 million robots, most of which work on welding, assembly and handling tasks. There have been very few robot arms being used in varied industries like agriculture, industries or warehouses apart from electronics and automotive units, due to the limitation of computer vision.
Robotics brings together a wide range of different machines including Pepper partnering with soft-bank; the Boston Dynamics humanoid robot Atlas, which can do backflips in movies and television and a plethora of humanoids and Bots that leave the human mind with awe and inspiration to achieve new tech heights. Much that the technology that powers robotics continues to achieve new pinnacle; people not familiar with the developments tend to hold polarized views, ranging from unrealistically high expectations of robots with human-level intelligence, or an underestimation of the potential of new research and technologies. Over the past years, questions have been asked about what is actually going on in deep reinforcement learning and robotics industry. How are AI-enabled robots different from traditional ones and their underlying potential to revolutionize various industries, what is the new excitement the robotics industry holds for the future. These questions point towards the challenging world of robotics and how difficult it can go to understand the current technological progress and industry landscape, to enable tech giants and newbies alike to make predictions for the chúng tôi what is about the robot evolution from the automation to autonomy? What started off as a quest to make routine work easy through automation has come a long way towards full robot autonomy? AI brings a game changer approach to robotics by enabling a move away from automation to true self-directed autonomy. When the robot needs to handle several tasks, or respond to humans or changes in the environment, it essentially needs certain levels of autonomy. The path from autonomy has been an uphill but a truly worthwhile change. According to a source, the evolution of robots can be explained by burrowing case studies from the autonomous car space. For an easy explanation of the process underlined below, robots are defined as the programmable machines capable of carrying out complex actions automatically. • Level 0 stage is also called as the No automation stage where people operate machines, there is no automation without any robotic involvement. • Level 1 stage is the driver assistance level, where a single function or task is automated, but the robot does not necessarily use information about the environment. Traditionally, robots are deployed in automotive or manufacturing industries programmed to repeatedly perform specific tasks with a high precision and speed. • Level 2 stands for partial automation where a machine assists with certain functions, using sensory input from the environment to automate some operational decisions. Examples include identifying and handling different objects with a robotic vision sensor. In this stage, robots lack the ability to deal with surprises, new objects or changes. • Level 3 is the Conditional autonomy where the machine controls the entire environment monitoring, but still requires a human’s intervention and attention for unpredictable events. • Level 4 is the high autonomy stage where the machine is fully autonomous in certain situations or defined areas. • Level 5 is the complete autonomy level powering the machine with full automation in all situations.Today, a majority of robots deployed in factories are non-feedback controlled, or open-looped implying that their actions are independent from sensor feedback as that happens in level 1 stage as discussed above. Few robots in the business act and take commands based on sensor feedback as that happens in Level 2. A collaborative robot, or co-bot, is designed to be more versatile empowered to work with humans; however, the trade-off is less powerful and happens at lower speeds, especially when compared to industrial robots. Though a co-bot is relatively easier to program, it is not necessarily autonomous to handle. There is often a need of human workers to handhold a co-bot every whenever there is any change in the environment or the task. Pilot projects integrated with AI-enabled robots, have started to become a regular feature incorporating a Level 3 or 4 autonomy, like warehouse piece-picking. Traditional computer vision cannot handle a wide variety of objects like that in e-commerce because each robot needs to be programmed beforehand and each item needs to be registered. However reinforcement learning and deep learning has enabled robots to learn to handle different objects with minimum human assistance. In the times to come, there might be some goods that robots have never encountered before which would need a support system and a demonstration from human workers bringing the level 3 of automation. In the times to come, improvements will be seen into algorithms to get closer to full autonomy as the robots collect more data and improve through trial and error in Level 4. Taking a clue from the autonomous car industry, robotics startups are additionally taking different approaches to autonomy for their robots. Some aspects believe in a collaborative future between robots and humans, and focus on Level 3 mastery. While in a fully autonomous future, skipping Level 3 and focusing on Level 4, and eventually on Level 5 will be difficult to assess the actual level of autonomy.Taking the brighter side, robots are being used in a lot more use cases and industries than ever before. AI-enabled robots are running warehouses, in a semi-controlled environment, picking up critical pieces that are fault-tolerant tasks. On the other hand, autonomous home or surgical robots will be a reality of the future, as there are uncertainties in the operating environment, where some tasks are not recoverable. With the change in time, the human eyes will see more AI-enabled robots being used across industries and scenarios as reliability and technology precision improves. The world has seen only about 3 million robots, most of which work on welding, assembly and handling tasks. There have been very few robot arms being used in varied industries like agriculture, industries or warehouses apart from electronics and automotive units, due to the limitation of computer vision. Over the next 20 years, the world will witness an explosive growth and a changing industry landscape which will bought by the next-generation robots as reinforcement learning, cloud computing and deep learning unlock the robotic potential.
Ghost Bat Drones Could Fly Alongside The Next Generation Of Air Force Fighter Jets
The US Air Force is looking for a new way to win fights in the sky, and is turning to drones that can escort crewed fighters to do so. To explore the concept, the US Air Force is eyeing the idea of using a drone called the Ghost Bat, which was built for the Royal Australian Air Force. Speaking at an August event with the head of the Royal Australian Air Force, US Air Force Secretary Frank Kendall suggested that the MG-28 Ghost Bat, or a variant, may fly into combat alongside future US fighters. The remark was first reported by Breaking Defense and hints at a future of international design for the loyal wingmate aircraft of tomorrow.
“I’m talking to my Australian counterparts in general about the [Next Generation Air Dominance] family of systems and how they might be able to participate,” Breaking Defense reports Kendall saying. In that context, Kendall continues, the Ghost Bat “could serve ‘as a risk reduction mechanism’ for NGAD’s drone capability.”
Next Generation Air Dominance is a long-in-development Air Force program and concept for designing aircraft that will fight in the skies of the 21st century. Historically, the Air Force has invested a great deal of effort into developing generations of fighter jets, with each wave flown alongside fighters from the previous and succeeding eras until deemed fully obsolete and phased out.
The MQ-28A Ghost Bat naming event in March in Queensland, Australia. LACW Emma Schwenke
Generations of jetsConsider the F-4 Phantom, a third-generation fighter that first entered military service in 1958, where it flew alongside the second-generation F-100 Super Sabre. The US retired the F-4 Phantom in 1996, after it flew alongside fourth-generation planes like the F-15 and F-16. Today, those fourth generation fighters fly alongside fifth-generation planes like the F-22 and F-35.
That pattern of development, which matched the pace and limits of aircraft development in the 1950s through 1990s, meant planes being flown for decades, despite becoming more and more obsolete as newer aircraft entered service at home and abroad.
“The Next Generation Air Dominance program is employing digital engineering to replace once-in-a-generation, mass-produced fighters with smaller batches of iteratively-upgraded platforms of multiple types,” declares an Air Force acquisition report from 2023-2023.
Ghost Bat is a product of the Loyal Wingman program, which set out to design a dependable drone escort for fighters. This program is a way for the Air Force to iterate on plane design without committing to decades of service from the drones.
Loyal wingmateIn the 2023-2023 report, the Air Force described Next Generation Air Dominance as a way to achieve air superiority in challenging conditions. At present, the air superiority mission is performed by crewed fighters like the F-22 and F-15, whose pilots risk their aircraft and their lives when fighting against enemy aircraft and anti-air weapons. Instead of building a single new fighter to replace F-15s and F-22s, the Air Force wants to borrow from the iterative design of the automotive industry, making drones with open architecture that can be more quickly developed, all in the name of improving the Air Force’s ability to survive, kill, and endure in the face of enemy aircraft and weapons.
This survival will come as part of a mixed fleet of drones and crewed aircraft. Under the Loyal Wingman program, the Air Force has worked for years to develop a drone that can fly and fight alongside a crewed aircraft. Loyal wingmates, as envisioned, will fly alongside F-22s and F-35s, and any crewed aircraft that replaces the stealth jets may be designed with loyal wingmates in mind.
What is the Ghost Bat?The Ghost Bat is an uncrewed plane that is 38 feet long, with a flight range of 2,300 miles. Boeing, which makes it, says that the drone will incorporate sensor packages for intelligence, surveillance, and reconnaissance, and expects it to perform scouting missions ahead of other aircraft, as well as being able to detect incoming threats. In addition, the plan is for the Ghost Bat to employ “artificial intelligence to fly independently or in support of crewed aircraft while maintaining safe distance between other aircraft.”
When the Royal Australian Air Force announced the Ghost Bat in March, they said it was the “first Australian-built aircraft in more than 50 years.”
The name, selected from a pool of over 700 possibilities, is a tribute to the only carnivorous species of bat in Australia; they are hunters that use both eyes and echolocation to hunt prey. As the announcement from the RAAF explained, Ghost Bat was chosen as a name because ghost bats are the only Australian bat that can prey on both terrestrial and flying animals. In addition, the RAAF pointed to the drone’s possible use in electronic warfare, a mission already carried out in Australia by a unit with a ghost bat symbol.
None of this offers a wealth of information on what the Ghost Bat actually does, but that’s sort of the point. What the Ghost Bat most needs to be able to do is be an uncrewed plane that can fly safely with, and receive orders from, crewed aircraft. To meet the goals of Next Generation Air Dominance, the Air Force wants planes that can be easily adapted to new missions and take on new tools, like sensors or electronic warfare weapons, or other tech not yet developed.
Boeing built the Ghost Bat for the Loyal Wingman program, but it’s not the only loyal wingmate explored. The Kratos Valkyrie, built for the Air Force and tested as a loyal wingmate with the Skyborg autonomous pilot, has already seen its earliest models retired to be museum pieces.
While these are distinct aircraft, the flexibility of software and especially open-architecture autopilots means that an autonomous navigation system developed on one airframe could become the pilot on a different one. It is this exact modularity and flexibility the Air Force is looking at, as it envisions a future of robots flying alongside human pilots, with models numbered not in generations but years.
Synaptics And Pilotfish Collaborate To Develop Next Generation Mobile Phone Concept
Synaptics and Pilotfish Collaborate to Develop Next Generation Mobile Phone Concept
SlashGear has received a press release and an internal document about Onyx, a collaborative cellphone project by touch-sensor specialists Synaptics and industrial design wizards Pilotfish. Unlike many concepts, where a sleek, headline grabbing shell either runs standard software or nothing at all, or a new platform runs on bland reference hardware, part of the charm of Onyx comes from the harmony of the software/hardware interface. In fact it’s this interface – and your interaction with it – that potentially makes Onyx the product of 2006.
“The real meaning of this product is about opening up the channels between hand, eyes, and device, and giving people access to actions and information in a way not possible with conventional buttons” [Brian Conner, Pilotfish]
To call the Onyx touchscreen-based is to do it a disservice; in fact, it uses Synaptics innovative ClearPad technology, the first transparent touch-sensitive capacitive sensor. ClearPad is capable of recognizing not only points and taps but also shapes and complex movements, together with multi-point input. At 0.5mm thick, the sensor layer can recognize touch and gestures through up to 1.6mm of plastic, making it far more durable and optically clear than traditional multi-layer touchscreens. And above and beyond those touchscreens it can recognize one or two finger contact, a finger used on its side, or even different body parts; a phone call to Onyx can be answered by simply holding it to your cheek, messages sent by swiping them off the screen with the whole finger.
Clever stuff, but the joy of Onyx comes from the cutting-edge industrial design and user interface design package provided by Pilotfish. Working closely with Synaptics to eke out the best of ClearPad’s capabilities, Pilotfish have followed the philosophy that hardware and software are not two separate fields but rather interrelated parts of the overall experience of a product.
“The design statement of the physical product itself is very simple: it’s all about the living, interactive surface that presents itself to the user and everything else is secondary. The main display and interaction surface is a curved optical panel over the large LCD display. The life underneath the surface is housed in a one-piece aluminum housing” [internal document]
A system of simultaneously running, dynamically inter-communicating applications that, rather than being static menu-based, are task-oriented, the joy of gesture control is that it removes the unnecessary interruption of buttons and icons. Tasks can be closed by gesturing an “X” over them, for instance, and blowing a kiss to the screen can speed-dial your partner (or lover).
Synaptics and Pilotfish see Onyx as a tool assisting OEMs in visualizing a fundamentally new form of user interface. They might not put it in so many words, but they’re part of a new breed of technology company that recognizes that as functionality in mobile devices expands then the interface by which we access it must evolve too. The pool of power-users willing and capable of deciphering endless menus and sub-menus remains a minority amongst normal consumers, and if the latter are to be persuaded to upgrade for reasons other than “world’s thinnest” then it’ll take more than redesigned iconography to do it.
Oculus Rift S Review: The Second Generation Of Pc
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UPDATE, 05/21: Our original Rift S model experienced a severe crash bug that we’d mentioned as an aside in the original review. Since then, Oculus sent us a replacement that doesn’t seem to exhibit the same behavior, but it looks like plenty of people in the Oculus subreddit are experiencing similar problems to my original unit. Thus I’d highly recommend holding off purchasing a Rift S until the problem is fixed, or at least until the root of the problem is sussed out. We’ll keep an eye on the situation over here, but there are way too many posts about the issue to ignore.
The review below still generally applies, but might as well issue this important caveat up front.
An angel’s touchThe Oculus Rift S has three key selling points. Problem is, only one of the three is an unequivocal improvement upon the original Rift. The other two “improvements” come with significant caveats, enough that you could argue they’re not improvements at all.
But we’ll get into that later.
IDG / Hayden Dingman
For now, let’s start with the Oculus Rift S’s one unabashed success: Comfort. Despite releasing on the same day, the Quest and Rift S have very different designs. The Quest adheres closely to the original Rift, with semi-rigid plastic straps on the sides and top that meet in a head-cradling triangle at the rear. And it’s comfortable enough, with the original Rift beating out the HTC Vive’s elastic straps when it released in 2023.
IDG / Hayden Dingman
But at least in one regard, raw comfort, the Oculus Rift S easily surpasses its predecessor—and Quest too, for that matter. It’s also the aspect Oculus has talked up the least, which brings us to selling points two and three: Optics and tracking. And it’s here that the narrative around the Oculus Rift S gets a bit more complicated.
A flair for lensesIDG / Hayden Dingman
New lenses are probably a contributing factor there as well—and in reducing so-called “god rays.” The original Rift was plagued by lens artifacts, streaks of light that appeared whenever a bright light was set against a dark background i.e. white text on black. The Rift S isn’t wholly free of this ugly byproduct, but the streaks are more diffused this time, and thus less noticeable.
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IDG / Hayden Dingman
That said, the improvements made to the Oculus Rift S optics are probably more important than the caveats. You’d be hard-pressed to notice the difference between 80Hz and 90Hz moment-to-moment, which renders that dip pretty meaningless. I feel similarly about the LCD screen, as I said. On paper it’s worse, but in actuality it’s imperceptible.
The field of view change, or a perceived field of view change, is the only concern that gives me pause. The Oculus Rift S does feel tighter to me, more like looking through binoculars—perhaps because the improved padding keeps the lenses further from my eyes? I’m not sure. Regardless, the increased resolution and diminished lens artifacts are a fine compromise for minor field of view changes in my opinion.
Swallow my doubt, turn it inside-outTracking is bound to be the most controversial choice Oculus made with the Rift S. Like Quest, the Rift S ditches Oculus’s old base station cameras—technology that dates to the Oculus Rift DK2—in favor of inside-out tracking.
IDG / Hayden Dingman
It’s easy to set up. That’s the main benefit. The original Oculus Rift retrofitted its position-tracking cameras to eventually work in a room-scale environment, but they weren’t designed to do that originally. They were meant for usage at a desk, seated, and Oculus only reacted when the HTC Vive forced the room-scale question. The Rift’s base station cameras didn’t track a very large area. You needed three to ideally cover the same space as the Vive’s trackers, and even then the Rift often encountered issues.
IDG / Hayden Dingman
The Oculus Rift S has one DisplayPort and one USB connection. Plug those in, and you’re done. That’s all the physical setup. No base stations, no additional cables.
IDG / Hayden Dingman
Controller tracking is far more problematic though, especially when compared to the Vive, which I’d consider the gold standard. Base stations are cumbersome, but allow controllers to be tracked independent from anything else. This is true of both the Vive and (with the caveat that it rarely worked as seamlessly) the original Rift as well. With base stations, you can put your controller in a box across the room and as long as the base station can see it, you’ll be able to see it in VR as well. A better real-world example: If you put your hands behind your back, they don’t magically disappear.
But the dead zones are there, and they’re noticeable. I still spend quite a bit of time in Google Earth VR, and thus noticed a glaring blind spot under the chin, where you hold a controller to display Street View images. The Oculus Rift S hated that area unless I held a controller slightly away from my chin, in view of the front-facing cameras.
IDG / Hayden Dingman
“Okay Hayden,” I hear you say, “the same problems crop up with Oculus Quest and you gave it a pass there. I’m reading your review and you said blind spots are edge cases, ‘worth ditching the base stations and giving you the freedom to relocate to a new room on-the-fly.’ Why’s the Rift S held to a different standard?”
First, let me say how much I appreciate that you read both reviews today, hypothetical reader. I know they’re long.
But second, it’s a matter of expectations. The Oculus Rift S does track Touch controllers as well or better than Quest, and it is fantastic to ditch the cumbersome base stations. Writing about the Oculus Rift S in March, I said it was “good enough,” the same phrase I’ve used to describe the Quest—meaning good enough that most people wouldn’t even notice the moments it breaks.
IDG / Hayden Dingman
Point being, if you’re hardcore enough about VR that you prefer to hook up to an expensive gaming PC (and deal with the accompanying cable) rather than opt for the less powerful (but self-contained and wireless) Oculus Quest, you’re also more likely to care about flawed controller tracking—and less likely to care about mounting base stations to your wall to ensure peak performance.
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That doesn’t mean the original Rift was better, because it wasn’t. The HTC Vive, though? I’d still prefer that and some wall-mounted Lighthouses, seeing as it’s fire-and-forget simple to set up and delivers flawless tracking every time, no real edge cases to speak of. If I’m opting for an enthusiast-grade experience, I want an enthusiast-grade experience. No caveats.
Bottom lineThe Next Wave Of Google Algorithm Changes
It sounds like Google’s algorithm is going to change again, and while I don’t believe in chasing the algorithm, I do find the impacts on our industry interesting, but even more so the impact it has on user behavior. The Wall Street Journal’s coverage of changes to Google to get people to stay on site longer to compete against Facebook may actually be a bad strategy for Google and more importantly bad for people. The article implies Google is slowly moving to an answer engine to compete against Siri, and becoming more semantic in nature. While I think for the end user this may be a great idea, it may actually hurt Google financially and it will be interesting to see how this evolves.
A Primary Source of RevenueHere’s an example scenario. Say I searched for “things to do in Toronto”. Google’s results may include:
A list of recommended hotels.
The top 5 attractions
The population
The geographic size
Other facts about the city.
The hotel list doesn’t really change from local results, but the top 5 attractions, what impact does this have on tourism? Instead of getting a link to a page that may be able to cover a great variety of events, and attractions, we’re now stuck with Google’s Top 5 list. Whether we realize it or not Google is slowly turning our lives into lists, and if you’re not on the list you’re not relevant.
This is why there was a boom in local search when this was introduced. There will be a boom again as it becomes clearer what types of lists Google will focus on. How about entertainment? Or restaurants? Or events? How much of a coincidence that most of these things also have clear schema’s developed?
The Impact to Your WorldWe know changes to the algorithm also have real world impact as there are countless stories of complaints every time the algorithm changes. Users trust Google so implicitly they don’t question if Google still deserves that trust. As Google gets better at recommending answers and things to do, will users actually get dumber? Will users become more homogeneous? Google already starts to suggest what you should search for as you type, and now they display the results.
Even if Google says they see 20% of searches as new and unique, what volume actually makes up the short head? Further is the head growing? Or are there specific categories of searches that are growing and easily classified? I assume we’ll know as we start to see these search results show up.
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