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What should you know about Thunderbolt 4?

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Did Intel Fool Us? - Thunderbolt 4

Flux

With a bit of creative thinking, Webflow can be used for so much more than marketing websites.

When we previewed this dashboard in our Instagram stories last week, you guys went crazy, so we obliged--here's how we did it.

Let us know if there's any kind of other Webflow tutorials you'd like to see from us!

We recently wrote a blog post showcasing some of the most stunning Webflow websites out there. Give it a read: https://bit.ly/3uIJQyG

Timestamps:
00:00 Intro
00:45 Why we built a dashboard
1:29 How it works
3:10 Page structure
5:15 The custom code

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Learn how to build custom websites with Webflow FAST:
https://bit.ly/WebflowWebclass2020​​​​​
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Find me on other social media platforms:
Instagram: https://www.instagram.com/ransegall/​​​
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#webflow​​​​ #webdesign​​​​ #websitedesign​​​

Thanks for watching the video!{{SUBSTRING}}

How To Create a Simple Dashboard With Webflow | WEBFLOW TUTORIAL:

dashboard of the cockpit and leave them overnight and

TKOR

Check out our LIQUID METAL fidget spinner video:  https://goo.gl/4nj1eM

This instant ice experiment is great for those interested in: water bending, freezing water with magic, instant colored ice, how to make instant ice, dry ice experiments, how to make snow cones , and much more!

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How To Make RAINBOW Instant Ice! TKOR's Freezing Water With Magic Water Bending Trick!

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Xclaim, a daughter company of Ruckus, is shaking up the small business wireless game right now with this R500 variant, the XI-3.

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Intro Screen Music Credit:
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time that we could probably actually get 

brand-new storage server with them click 

open the box for an x i3 the first thing 

phone what oh and I guess there are also 

some accessories in there but I you know 

because my didn't pick my jaw up off the 

daughter company of ruckus the makers of 

wireless gear that you're most likely to 

darn similar to the ruckus r500 it's got 

even the power draw is rated exactly the 

before that basically brings up a how-to 

guide then you install the Harmony Forex 

clean app password protect the app which 

network and that was the first stumbling 

Xclaim XI-3 Indoor AP - Your Next Wireless Access Point

two exploratory tasks to get familiar with the  dashboard followed by two tasks that gauge  

two exploratory tasks to get familiar with the  dashboard, followed by two tasks that gauge  

ACM SIGCHI

Visual, textual or hybrid: the effect of user expertise on different explanations
Maxwell Szymanski, Martijn Millecamp, Katrien Verbert

26th ACM International Conference on Intelligent User Interfaces (IUI '21)
Session: User Experience

Abstract
As the use of AI algorithms keeps rising continuously, so does the need for their transparency and accountability. However, literature often adopts a one-size-fits-all approach for developing explanations when in practice, the type of explanations needed depends on the type of end-user. This research will look at user expertise as a variable to see how different levels of expertise influence the understanding of explanations. The first iteration consists of developing two common types of explanations (visual and textual explanations) that explain predictions made by a general class of predictive model learners. These explanations are then evaluated by users of different expertise backgrounds to compare the understanding and ease-of-use of each type of explanation with respect to the different expertise groups. Results show strong differences between experts and lay users when using visual and textual explanations, as well as lay users having a preference for visual explanations which they perform significantly worse with. To solve this problem, the second iteration of this research focuses on the shortcomings of the first two explanations and tries to minimize the difference in understanding between both expertise groups. This is done through the means of developing and testing a candidate solution in the form of hybrid explanations, which essentially combine both visual and textual explanations. This hybrid form of explanations shows a significant improvement in terms of correct understanding (for lay users in particular) when compared to visual explanations, whilst not compromising on ease-of-use at the same time.

DOI:: https://doi.org/10.1145/3397481.3450662
WEB:: https://iui.acm.org/2021

Pre-recorded presentation videos for IUI 2021.

explanations, and more specifically how user  expertise has an influence on perceiving them.  

My research was done together  with Martijn and Katrien, both  

from the Augment Research Group at the KU Leuven.

So we find ourselves in a field of  explainable artificial intelligence  

or XAI for short. The main goal of XAI is  to unravel the black-box of AI algorithms,  

and make certain parts of such algorithms  transparent to end users using explanations.  

These explanations can address various parts  of such algorithms, such as the output,  

what input parameters there are, and how  the input parameters have an influence  

on the output. For example here we  see a simple textual explanation  

that shows us why a certain post was recommended  to us on social media. Now realistically for me  

it would be more pictures of food, because  I like food, but that's besides the point.

Next we see an example of a visual explanation,  where this importance map shows us which parts of  

the image contribute to the outcome of the  underlying algorithm. So clearly there are  

many use cases, both theoretical and in practice.  However literature often discusses the positives  

of explainable AI. While there certainly are many  benefits and even needs for XAI, there are also  

some drawbacks to keep in mind. One such drawback  is that users build mental models of a system with  

the way they perceive and interact with it. So the  type of explanation chosen can strongly influence  

the way users perceive the same underlying  algorithm. And besides that, research also  

points out that user type also plays a big factor  in the way users perceive the same algorithm.  

So because this is a scarcely research topic, we  decided to explore the effects the different type  

of explanations have on perceiving the same  underlying algorithm, and more specifically,  

how this is influenced by user expertise. So  to do this we looked at differences in user  

interpretation and their personal preference. We  also measured other parameters, but for that i  

would refer you to our paper. Now the question is,  did we find a big gap between expertise groups?  

Well we certainly did! And that's why we also  decided to explore a different option on how we  

can minimize this gap between different expertise  groups. So that's for our third research question.  

So for the first iteration we developed  two common types of explanations,  

the first one being the textual one and the  second one being a more visual one using  

partial dependence plots which are used quite  often both in literature and in real use cases.  

Both these explanations convey  the same type of information  

regarding which input parameters are present, how  these parameters currently impact the prediction  

model, and how changing these parameters  would influence the outcome of the model.

To test the differences between two types of  explanations, we set up a between subject study  

with 10 experts and 10 non-experts.  During the study users had to perform  

their understanding of the explanations. And  the results we found were quite interesting.

Looking at the number of correctly answered  insight-tasks we see that non-expert users  

struggled quite a bit with the visual  explanations, more so than with the textual  

one. This isn't all that surprising as graphical  information requires more effort to interpret  

and might be more difficult for non-experts to  do. However, when looking at preferences we still  

see that the majority of both groups still  prefer the visual explanations. So do users,  

and mainly non-expert users, prefer the type  of explanation that they perform worse with?  

Seems rather strange.. Well, this can be explained  by looking at the think-aloud study logs.  

There we see that at least seven non-expert users  followed a flawed backwards-oriented reasoning.  

Under the classification of Croskerry et al.,  this falls under what they call System-I thinking,  

which is described as fast, low-effort and  heuristic-based. However, research by Lim et al.  

concluded that for inexperienced users,  which in our case are the non-expert users,  

System-I thinking might lead to confirmation  bias, where an incorrect hypothesis  

gets confirmed by selectively looking for  information that supports it. So that is why  

non-experts felt that the visual explanations  were more helpful in conveying the information  

even though they were interpreting  this information incorrectly.

Another issue we discovered with non-experts, was  the lack of exploration using visual explanations.  

When looking at the research of Tsai et  al., they state that unfamiliar information  

might induce a reinforcement  effect, that causes users to avoid  

interacting with various content. This  explains why the lack of exploration with  

non-experts is stronger with the visual  explanations than with the textual ones.

Now when looking at the expert users, we see  that at least seven of them followed  

a deductive reasoning approach, where they first  explore the given information to deduce a possible  

answer, and a reason about their correctness  of it afterward using their own knowledge.  

This deductive reasoning falls under the System-II  thinking, which is considered to be slower high  

effort and analytical. It is consequently less  prone to cognitive biases. So there is a clear  

hurdle to overcome regarding non-expert users and  their System-I thinking, and them still preferring  

the visual explanations. So how can we address  this? One solution that we came up with are hybrid  

explanations, that essentially combine the  aforementioned visual and textual explanations.  

While adding this new textual explanation does not  introduce any new information, we hypothesize that  

it will aid users and correctly understanding  the visual explanations that are also there.  

So to test our hypothesis we conducted  a second user study with 10 new experts  

and 10 new non-experts. This time, they had to  perform the same two exploratory tasks and the  

same two insight-tasks they also had to perform  in the first user study. However, this time they  

had to do it on the hybrid explanations. We  also compared these results with the previous  

visual explanation results the ones that had  the most issues that needed to be addressed.

So, did the hybrid explanations improve upon the  visual ones in terms of correct interpretation?  

The answer is most certainly: yes. For non-expert  users the addition of textual explanations  

allowed some users to correct their  wrong understanding of the graph above.  

Additionally, it also allowed them to be more  confident in exploring the dashboard, so this  

also partially addressed the lack of exploration  that we found with the visual explanations before.  

Expert users also benefited from the addition of  textual explanations, albeit in a different way.  

For them, the textual explanations functioned  more as a reassurance that they were correctly  

interpreting the visual explanations. Those  users stated that after looking at the textual  

explanations once, they felt more confident  in using the visual explanations afterward.

So what are the key takeaways from our research?  First of all, we see that user expertise is  

an important factor by looking at how users  perceive your explanations. Different expertise  

groups have different needs, expectations,  as well as limitations to take into account.  

Some of the limitations that we found  were more tied to the non-expert users,  

which were for example the reinforcement  effect that caused a lack of exploration,  

as well as the confirmation bias, which led to  incorrectly interpreting the visual explanations,  

more so than the textual ones. So  definitely take expertise of your  

target demographic into account  when designing your explanations.

Secondly, don't assume that all users will  understand your visual or graphical explanations  

correctly, or the way you intended it. So  make sure you provide additional information  

if you know your target demographic consists  of mainly non-experts. In our research,  

we explore the addition of textual explanations.  However, we advise you to also look into different  

methods such as adding tutorials examples and  so on that can also potentially aid users.

So this wraps up my presentation! I would  like to thank you for your attention,  

and please feel free to ask any  questions. Thank you very much!

Visual, textual or hybrid: the effect of user expertise on different explanations

of technology, one of the key selling points is,

USB 3.0 is not the previous generation technology

that Intel was also referring to the version of USB 3.0

that is 10 gigabit per second, not 20 gigabit.

Thunderbolt 4 actually has the exact same transfer speeds

So then is there any real reason to get excited?

While it was already the maximum overall speed,

some Thunderbolt 3 ports only supported speeds of up

to 16 gigabits per second for PCI express devices.

of high performance devices like external storage solutions

to 32 gigabits per second, with Intel claiming

if you're a video editor loading tons of footage

onto your external storage device from a camera,

or if you're just someone who moves a lot of files

And even if you're not constantly shuffling huge amounts

of data back and forth, Thunderbolt 4 offers the ability

to connect two, 4K displays or one 8K display.

And with all the multitasking we're doing these days,

driving multiple high resolution external monitors

on an ultra light notebook, could be pretty convenient.

but that wasn't the case across the board.

So the summary version is that Thunderbolt 4

which is double that Thunderbolt 3 supported,

and it will allow input devices like keyboards or mice

that are connected via a Thunderbolt 4 dock

Surprisingly, this didn't always happen before,

even though it's something we've taken for granted over USB

There's also a requirement for lightweight laptops

that at least one port to get Thunderbolt 4 certification

on any ultra portable that supports Thunderbolt 4.

which hasn't made deep in-roads into the market just yet,

but probably will over the next year or two.

like Thunderspy which made headlines in mid 2020.

And also that the cables should work to up to two meters,

so you shouldn't need active cables at or below that length.

That'll hopefully drive costs down a little bit.

is still an expensive protocol compared to USB though,

to tell which devices support Thunderbolt 4.

Now Intel says that all you have to do is look

for the Thunderbolt icon but it isn't always obvious

whether the sticker indicates Thunderbolt 4

and they use exactly the same Type-C connector.

So you'll wanna pay extra close attention

to those spec sheets if you're in the market

The first computers to offer Thunderbolt 4 are going

from late 2020, which support the new protocol natively.

But in the meantime, you can always just try

if 10 gig USB is really too slow for you.

I mean, you know, who has an 8K camera anyway.

Checkout Privacy, the tool that makes it super easy

Privacy masks your real bank information,

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Test your pronunciation!

“dashboard”