Echo Zhao: 我是Echo Zhao，您正在收听EE Times On Air。
BRIAN SANTO: …And I’m Brian Santo, EE Times Editor in Chief, and this is your Briefing for the week ending November 15th.
BRIAN SANTO: 我是EE Times的主编Brian Santo，接下来是截至11月15日的本周播报。
Last week, Junko Yoshida and I were in Shenzhen attending the Global CEO Summit, where we hobnobbed with top executives of companies from all around the world. This week’s episode will be dedicated to interviews we conducted at the event, which touched on every major trend in electronics today, including 5G wireless, advanced chip design and manufacturing, and artificial intelligence.
上周， Junko Yoshida和我在深圳参加了全球CEO峰会，我们与来自世界各地的公司高层们会面。本周的节目将专题报道我们在这次活动中进行的采访，内容涉及当今电子领域的每个主要趋势，包括无线5G，先进的芯片设计和制造，以及AI。
During this episode, we’ll hear from executives from companies based in the US, Europe, and China, including one of the world’s oldest and most prestigious industrial and electronics companies — Siemens — and one of the world's youngest and most intensely scrutinized AI startups — Graphcore.
All that and more coming up.
The first bit of news Junko and I heard when we landed in Shenzhen was of a possible ceasefire in the Trump Administration’s trade war against China. The news — as such — was even more tenuous than that. A spokesman for China’s commerce ministry said that both the US and China would have to suspend tariffs as prerequisite for the so-called "phase one" trade deal that President Trump incorrectly said he had forged with China last month.
Absent any progress in negotiations, tariffs will remain in place, as will US efforts to ban sales of US chips to Chinese OEMs. Chinese executives we spoke to said they'd prefer to keep buying the best chips they can find, which are often enough being sold by US companies, but since they can’t buy from Americans, they’re turning to other suppliers. And if those products are second-best, well, so be it.
Chinese companies appear to be holding out hope for some resolution to the trade war, however. We sat down with respected industry veteran Charles Tan. Here’s what he had to say about it.
不过一些中国公司似乎对贸易战的解决持乐观态度。 我们与受人尊敬的行业资深人士Charles Tan(谈荣锡)座谈。来听听他对此事必须想要表达的看法。
CHARLES TAN: My personal opinion is that China and US or, you know, American companies, it’s so difficult to decouple from each other. So one thing I think you know, it's probably the end of the honeymoon, but the marriage still exists. We need each other. And certainly if we are focusing rather than taking the share from the other side, if we can work together much closer, smarter, we probably can really increase the pie. And at the end of the day, every party enjoys.
CHARLES TAN: 我个人认为，中国和美国，或者说美国公司，彼此之间是很难分开的。我想你听过这种说法，蜜月虽然结束了，但婚姻仍然存在。我们需要彼此。 当然，如果我们关注的不是从对方手中抢夺蛋糕，那我们还可以更紧密、更明智地合作，这样我们也许真能增加蛋糕的分量，最终让每一方都获利。
BRIAN SANTO: We’ve heard similar things from American executives, too, but this trade war has been grinding on for more than a year, and every hint of a resolution thus far has been followed by another setback in negotiations.
BRIAN SANTO: 我们也从美国的高管那里听到了类似的话，但是这场贸易战已经持续了一年多，到目前为止，关于解决方案的每一个暗示都伴随着一次次的谈判被挫败。
For every optimist like Charles Tan, Junko and I encountered someone equally pessimistic. We were let in on a joke that seems to be making the rounds within China’s high-tech industry: Donald Trump must be China’s best friend – the joke goes – after all, he’s helping China’s electronics industry to become self-sufficient faster than it was planning to.
有像Charles Tan这样的乐观主义者，同样，我和Junko也遇到了对此事持悲观态度的人。 我们开了个玩笑，这个玩笑似乎在中国高科技产业中也流传着：特朗普一定是中国最好的朋友——玩笑是这样的——毕竟，他正在帮助中国电子行业按照比原本计划更快的速度实现自给自足。
But what if the trade war does get resolved? Would business go back to the way it was? The responses Junko and I heard from several Chinese electronics industry executives was: maybe, but probably not, because the damage is already done.
但是，如果贸易战得到解决，又该怎么办？ 行业还会回到原来的状态吗？ 我和Junko，以及我从几位中国电子行业高管那听到的回答是：也许吧，但也可能不会了，因为贸易战已经造成了伤害。
The Global CEO Summit is paired with another event called the – now I'm going to take a deep breath here – the Global Distribution and Supply Chain Leaders Summit. (BREATH) It’s an event for electronics distribution. Distribution is sort of the Rodney Dangerfield of the electronics industry – "Lemme tell ya, oof, distribution doesn’t get any respect, no respect at all."
全球CEO峰会与另一个活动——我先深呼吸一下——全球分销和供应链领袖峰会同期举行。这是以电子元器件分销商为主题的活动。 分销商们有点像电子行业的Rodney Dangerfield（编辑注：一位美国演员）：“不好意思，分销没有得到任何尊重，一点尊重也没有。”
And yet distributors are responsible for an enormous chunk of global electronics sales, and their in-house design experts — FAEs, or field applications engineers — are critical for supporting smaller electronics companies everywhere. So with so many distributors milling about, one of the hottest topics in Shenzhen was Texas Instruments. Recently, TI decided to cut its ties with most of its long-time distributors.
Once again, here’s Charles Tan, who, until recently, served as the president of the China Electronics Distribution Association.
CHARLES TAN: It’s shocking news. Their go to market in my opinion is go direct with the customers. So when you go direct to the customers, certainly it requires lots of resources. Today the technology, when you look TI or the TI technologies, probably will allow reciprocity for big customers or big companies to go direct to the customers. Whether this is going to work, I don't know. But they certainly will have an affect. Number one, if TI is able to successfully launch this go-to-market strategy, the question is, what about the other component manufacturers? So what about the existing channel partners? Are they motivated to promote TI technologies or products?
CHARLES TAN: 这真是令人震惊的消息。 我认为他们直面市场相当于是直接与客户对接。当你直接对接客户时，的确需要大量资源。 今天的技术，当你聚焦TI或IT技术时，这些技术可能会让大客户或大公司互惠互利，直面客户。 我不知道这条路是否行得通，可以肯定的是，必然会对行业产生些影响。首先，如果TI能够成功实施这个直面市场的策略，那么问题是，其他元器件制造商又会如何做呢？ 那么现有的渠道合作伙伴怎么办呢？ 他们是否有动力去推广TI的技术或是产品？
JUNKO YOSHIDA: That's the slip slide.
JUNKO YOSHIDA: 那是策略倾向。
CHARLES TAN: Exactly. So now whether it's a TI strategy to go get rid of some of the low-end products, they will focus on only those they're good at. So again, that's a question. So I think it's still too early to tell, right? Now, it's important to see how the other component manufacturers will do in a year or two.
CHARLES TAN: 正是如此。所以现在TI是不是在趁着推进新策略的机会摆脱某些低端产品，以便他们将只专注于自己擅长的产品。这同样是一个问题。因此我认为现在下定论还为时过早，对吗？ 现在重要的是，要了解其他元器件制造商在接下来的一两年内将会如何做。
BRIAN SANTO: Our colleague Echo Zhao is the chief analyst of AspenCore China, and was the moderator at the Supply Chain Summit. That was Echo introducing the show today, by the way. She explained that TI decided to drop six electronics distributors, including three top-tier players in China. We also asked Echo about the response to TI’s decision.
BRIAN SANTO: 我们的同事Echo Zhao是AspenCore中国区主分析师，也是此次供应链峰会的主持人。 顺便说一下，本期音频节目开场就是Echo做的介绍。Echo解释说，TI决定放弃6家电子元器件分销商，其中包括3家中国一线分销商。 我们也询问了Echo对TI作此决定的看法。
ECHO ZHAO: There were at least 1,000 — more than 1,000 —sales and FAEs lost their jobs. But an executive from TI's former distributor felt sorry about losing TI, but he said he still believes that TI is smart to do it. And he admired TI's move. He believes that ST and Qualcomm will do the same thing in the future.
ECHO ZHAO: 至少有1,000个——超过1,000个，销售人员以及FAE因此失业。 一位来自TI前分销商的高管对失去TI感到遗憾，不过他说仍然相信TI做的这个决策很明智，他欣赏TI的做法，并且认为ST和高通在将来也会做同样的事情。
JUNKO YOSHIDA: They will follow suit? Interesting.
JUNKO YOSHIDA: 他们会效仿TI吗？ 有意思。
ECHO ZHAO: So TI has given up the low-end market, so I mean TI knows even if they did not give it up, the market would have been eaten by China ICcompanies eventually. So TI prepared for this for six years, for more than six years. And TI has a very strong e-commerce system that will help.
ECHO ZHAO: TI放弃了低端市场，我的意思是，TI知道就算他们不放弃低端市场，低端市场终将还是会被中国IC公司吞下。TI为此决策做了六年以上的准备。 TI拥有的非常强大的电商系统也能有所助益。
JUNKO YOSHIDA: So the individuals, the smaller companies, could come in if they wanted via e-commerce.
JUNKO YOSHIDA: 因此，个人或是规模较小的公司可以通过电商进入这个行业。
ECHO ZHAO: Right.
ECHO ZHAO: 对的。
JUNKO YOSHIDA: Interesting. That's a theory.
JUNKO YOSHIDA: 有趣。这是一种理论。
BRIAN SANTO: EE Times and our sister publications did some additional reporting following last week’s Summits in China. STMicroelectronics told us it has no plans to trim its distributor list. Qualcomm has not yet responded to our questions, but also has made no public announcement that suggests it will emulate Texas Instruments.
BRIAN SANTO: 上周在中国举办了峰会之后， EE Times和我们的姊妹刊物做了一些其他报道。意法半导体（STMicroelectronics:）告诉我们，他们没有削减分销商名单的计划。 高通公司尚未答复我们的问题，不过也没有公开宣称会效仿TI。
Last year at the Global CEO Summit, it seemed that everyone was talking about artificial intelligence. This year, the conversation was all over the map. Keynoters talked about 5G, intelligent sensors, exascale computing, product design technology and mobile communications. …And, of course, artificial intelligence.
Graphcore is taking an approach the company insists is conceptually unique. Companies attempting to implement AI typically use GPUs, CPUs and FPGAs. Graphcore is building something it says is none of the above. It calls its device an Intelligence Processing Unit, or IPU.
Junko asked Graphcore CEO Nigel Toon: What exactly is an IPU?
Junko问Graphcore CEO Nigel Toon：IPU到底是什么？
NIGEL TOON: One of the ways to think about this is in conventional processing, which we've been doing for a very long time. Seventy-five years was the first electronic computer was made.
NIGEL TOON: 多年以来，我们一直使用常规处理方式 75年前就诞生了第一台电子计算机。
The word "computer" comes originally from people who did maths operations, right, and were replaced by machines. But we tell computers what to do, step by step in a program. Whereas now what we're doing is, we're learning from data. And, you know, so the machine is having to work and compute in a very different way from the conventional step through a program, follow a path in a program. If there is a program.
“计算机”一词最初源自于做数学运算的人，后来被机器所取代。 但是我们通过程序逐步告诉计算机该做什么。 现在我们正在做的事情是，从数据中学习。与通过程序实现的常规步骤、遵循程序路径不同，机器必须以另一种不同的方式来工作和计算。如果里面有设置程序的话。
But the program's actually very simple. Mainly what it is is, huge amounts of parallel compute that is going on. And the data structures that we really need to be able to build are very, very different. You know, it's not like take a big block of data and perform some operation on it. You know, take this block of pixels and paint them blue, for example. What you want to do is really be able to... It's almost like finding needles in haystacks.
You're looking for different strands of information and pulling those together, working which are the important ones. And so you need to be able to take a piece of data from here, bring it to the processor, do some compute, write the answer back somewhere else. So the data structures and the memory structures that you therefore need are very different. And computer architectures follow the data.
So if you look at how computers evolve, they've really evolved around what are the data structures you're trying to process on. So network processing, for examples. Streams of packets coming through that you can then handle in a nice, convenient way. Graphics processing the same. You know, large blocks of pixels that I need to work on. Typically the same operation that I'm doing across lots and lots of, a block of pixels. So single instruction, multiple data.
如果你看看计算机的发展方式，会发现它们实际上是围绕着你要处理的数据结构在发展。以网络处理为例，你可以以一种轻松、便捷的方式处理通过的数据流包。图形处理同理。你知道，我需要处理大像素块。 通常我在很多像素上执行相同的操作。 就是单条指令，多条数据。
What we now need is multiple instruction, multiple data. And we need to be able to do that with huge amounts of compute on what could be very sparse data. And so the architecture of the machine needs to be very, very different.
But you also need to design it in such a way that you don't push all of that complexity onto the programmer. The programmer just needs to be able to say, Look, this is my knowledge model. This is how, you know, the data's going to be structured. You know, make it work. And so we've built a... together with the processor, we've built a software system we call Poplar. We've developed those two very much together step by step to be able to actually take high-level descriptions and frameworks like TensorFlow or PieTorch and have them efficiently mapped onto the processor.
JUNKO YOSHIDA: Are there any Chinese AI chip companies you're paying attention to?
JUNKO YOSHIDA: 你是否关注过哪家中国AI芯片公司？
NIGEL TOON: I think there's a number of very well-funded AI chip companies in China. We obviously pay attention to many of the companies. I think somebody told me there's 70 companies trying to build chips for AI. But maybe this is the wrong approach. I always describe it as the "Italian rule of driving." The Italian rule of driving is, the rearview mirror doesn't matter. You don't need it. All you need to do is drive very fast and be ahead of everybody else, and what is behind you doesn't matter. Right? So I think that's kind of our attitude.
NIGEL TOON: 我认为中国有很多资金雄厚的AI芯片公司。我们显然是有关注到许多公司。 我想有人告诉我，有70家公司正在尝试为AI构建芯片。 但这个方向可能不太对。我总是将这种情况描述为“意大利驾驶规则”。 意大利的驾驶规则是，后视镜无关紧要，你用不上后视镜，你需要做的就是开得越快越好，超过其他车，在你车后的都不重要。对吗？ 我认为这就是我们的态度。
We started much earlier than many of the other companies. We've developed products; we've got products with customers; we're learning from customers already what's needed; our software is much more advanced; our architecture is much more advanced. And somehow what we've got to do is, we've got to run fast and make sure that we can keep our advantage and stay ahead.
I'd also describe it as, it's a bit like you go on a railway, but you don't want to go on somebody else's railway. You don't want to follow somebody else, right? You don't want to copy what somebody else is doing. You want to lay your own tracks and go in your own direction and have your own differentiated approach. And eventually, if you're right, people will follow you on your tracks.
也可以这样讲，这有点像你正在一条铁轨上，但是你肯定不想走在别人的那条轨道上。你不想只是跟着别人，对吗？ 不想复制别人在做的事。 你想要走自己的路，朝自己的方向前进，并且拥有自己的独特道路。最终，如果你的方向是对的，人们就会在你的这条轨道上来追随你。
BRIAN SANTO: When we asked how far this new IPU has penetrated the AI market, Nigel said, “We're just at the beginning.”
BRIAN SANTO: 当我们问到这个新的IPU目前在AI市场的渗透程度时，Nigel说：“我们还刚刚起步。”
Graphcore is spending half a billion dollars in this business over the next few years, however, to push this new computing architecture.
Toon told us that the industry today “feels like the dawn of microprocessors in 1970s” – which he wants us to know he was too young to remember. But what he meant, he said, is that he expects AI and devices like Graphcore’s IPU to help create a new round of Intels and Apples.
Toon告诉我们，当今的行业“感觉就像19世纪70年代微处理器带来的曙光” ——不过他希望我们明白，当时他还太小，以至于没能记得很清。 但他说，他的意思是，希望AI和Graphcore的IPU这样的器件能帮助创建新一批的“英特尔“们和”苹果“们。
One of the other major themes at the Summit was the introduction of 5G technology. Qorvo is one of the leading suppliers of integrated circuits that handle radio frequency signals. This is the stuff that makes wireless products wireless.
峰会的另一主题介绍了5G技术。 Qorvo是领先的处理RF信号的IC供应商之一。 这就是使无线产品之所以能变得无线的器件。
We spoke with Roger Hall, global general manager of Qorvo’s high performance products. I asked him, What are the biggest challenges that the industry is facing with 5G?
我们与Qorvo高性能产品的全球总经理Roger Hall进行了交谈。 我问他，对于5G，目前业界面临的最大挑战是什么？
ROGER HALL: The biggest challenge to start out with is from a market perspective. China's around 70% of the world's share of base stations. They believe that there are already around 86,000 radios, base stations, installed to date, with plans to be 130,000 by the end of the year. So the ramp is starting, but it's a significant ramp.
ROGER HALL: 首先面对的最大挑战是得从市场角度出发。中国部署的基站约占全球基站总数的70％。人们认为，到目前为止，中国已经安装了约8.6万个无线基站，并计划在年底之前安装完13万个。 所以市场已经开始爬坡了而且是个大坡。
They will be rolling out over a million radios, base stations, this next year. And so the challenge goes then the amount of just pure volume to be produced. And that's not just for the OEMs, but it's for all the supply chain. And so scale is a key thing. So being able to scale. And then that then... not only just the volume, but providing at a high quality and supporting the continued on-time delivery and support that they need as they ramp. So that's the first challenge.
From a technology perspective, what they're looking for is... and why is 5G important? It's about more capacity for the network. The amount of load that we generate from our smartphones. Or, with the next generation of 5G there's actually three elements they're focusing on: IoT, so it's the backbone, IoT; as well as the smartphones; as well as the man-to-machine connections or machine-to-machine connections. So those three elements create a lot of additional demand on the network.
从技术角度来看，人们正在寻找的是... 5G为什么如此重要？ 其实是关于更多的网络容量，我们从智能手机产生的负载量。 或者说，对于下一代5G，人们实际上关注的是三个要素：IoT——IoT可称得上是5G的基础；智能手机； 以及人机连接或机对机连接。这三个元素对网络产生了很多额外的需求。
BRIAN SANTO: I followed that up by asking him about the technological challenges.
BRIAN SANTO: 我随后向他询问了技术方面的挑战。
ROGER HALL: Because there’s many different use cases and many different applications, it creates different challenges for each one of those. If we just look at the cell phone, it's always about battery life; it's about the performance; it's about the dozens of bands it has to cover. And so then there's lot of need for filtering and for antenna tuning and for range to connect to the network. So there's many, many technical items that have to be overcome. From the antennas: where do they fit in the phone? How do I get them all in? To all the switching of all those bands. And then amplifying and cleaning those signals up so that you get high quality data.
ROGER HALL: 由于存在许多不同的用例和许多不同的应用，每类应用都带来了不同的挑战。 如果我们单看手机，那电池寿命总是挑战；性能也要提升；还要覆盖数十个频段。所以对于滤波、天线调谐，以及网络连接距离都有需求。有许多必须克服的技术问题。天线的问题：它们适合安装在手机的哪个位置？ 如何才能将所有天线全部装好？ 怎么解决所有这些频段的切换问题。然后是放大、清除信号，以便获得高质量数据的问题。
And again, as a personal user, we want our batteries to last. But as the IoT, they also want the units to last a long time. So they'll have different requirements of low latency and for many of the robotics items as well.
So the exciting thing with 5G is not just... is all these new markets are going to come up. There's lot of opportunities for innovations of many companies all over the world. Some people look at it as, it's a race to who's going to deploy first. I look it more as this is enabling of a lot of exciting new technologies that are going to be created.
5G令人兴奋之处不仅仅是，所有这些新的潜在市场都将出现。 全世界的许多公司拥有许多创新机会。有人认为，这是先到先得的竞赛。 我更认为它是因为——将开启许多令人兴奋的新技术。
And to your point, what are the barriers? It's about, How do you get all those signals in that little-bitty phone? And how do we get all that additional data through the network? So what they're rolling out in China is 2.6 and 3.5 gigahertz this year as the primary 5G bands. And with those 5G bands, they're broader bandwidth, which allows then a lot more capacity, which creates technical challenges. How do you have 200 megahertz of bandwidth, instantaneous bandwidth, in the past where it's been 10 to 20. Right?
对你来说，有什么阻碍？ 关于你如何在那小巧的手机中获取所有这些信号？ 以及我们如何通过网络获取所有其他数据？他们今年将在中国推出的2.6和3.5 GHz频段是主要的5G频段。借助这些5G频段，提供更大的带宽，从而能支持更大的容量，这带来了技术挑战。在过去只有10M到20M，你如何在现下拥有200兆赫的带宽，瞬时带宽？
So you end up with more complications within the phones, as well as more complications within the base stations. And how do we support those?
In the future, you're right, we'll see 4.9 gigahertz in China. Around the world, you'll see those similar bands, slightly different locations, and in some cases, as you said, millimeter wave, which creates a non-linear very, very complicated situation. There's been point-to-point and there's been defense applications, but mass deployment becomes a challenge.
在未来，你是对的，我们将在中国看到4.9 GHz的频率。 在世界各地，你会看到那些相似的频段，但位置略有不同，在某些情况下，正如你所说的，毫米波会产生极端复杂的非线性情况。 目前已经有点对点的，以及国防应用，但是大规模的部署成为了一个挑战。
So when what are the operators looking at us to help them solve? CapX is a huge issue. How do we deploy all of this new network at an affordable cost? And then after it's deployed, it takes lots of power. So they're looking at, from an OpX perspective, what can we do to help lower that energy usage? How do we make it get greener? And that's where GaN comes into play, where it's most more efficient of a broadband. And it's where the high efficiency switching comes into play and antenna tuning that we have on our cell phones, and these different things that help reduce the total amount of power consumed.
那么，什么时候运营商会寻求我们来帮助他们解决这些问题？资本性支出将是一个巨大问题。 我们如何以可承受的成本，来部署所有这些新网络？ 而且在完成部署之后，它还需要大量的电源。 因此，他们从运营成本的角度着眼于我们怎么做才能降低能耗？ 我们如何使其变得更节能？ 这就是GaN发挥作用的地方，它是宽带中效率最高的。 这正是我们手机上高效开关和天线调谐发挥作用的地方，这些不同部分有助于减少总功耗。
It's always about reliability. That's a key thing in this industry. You want to put them out there for five, ten, fifteen years and not be touched. And it's just about performance to those needs.
可靠性总是关键点，是这个行业的关键。 你希望能将它们放置在那里五年，十年，十五年，并且完好无损。 而这仅仅是满足这些需求的性能。
BRIAN SANTO: Junko and I took a walk through one of Shenzhen’s shopping districts. There were many storefronts touting the advent of 5G, many of them encouraging people to sign up with the major carriers for 5G phone services that weren’t even available yet.
BRIAN SANTO: 我和Junko去逛了深圳的一个购物区(编辑注：他们去的是华强北)。许多店面都在吹捧5G的到来，其中许多鼓励人们与主要运营商签订5G电话服务的合同，而这些服务甚至还暂未开通使用。
Product design has grown up in silos. Companies that design integrated circuits have had dedicated design tools. Companies that design mechanical products have had their own dedicated design tools. Of course, very many products combine electronic, electrical, and mechanical subsystems, so it’s been a long-term goal to unify all of these tools. The design industry is finally beginning to do that.
许多产品之间在互不交流的情况下设计出来。设计IC的公司拥有专用的设计工具。 设计机械产品的公司拥有自己专用的设计工具。 当然，很多产品都结合了电子、电气和机械子系统，因此统一所有这些工具将是一个长期目标。 设计行业终于开始往这个方向发展。
Tony Hemmelgarn is president and CEO of Siemens Digital Industries Software, which for a couple of years now has also owned Mentor Graphics. Key to the company’s vision of integrated manufacturing design is the concept of the “closed loop digital twin.” Junko sat down with Tony last week and asked him: What the heck does that mean?
Tony Hemmelgarn是西门子数字工业软件公司的董事长兼CEO，该公司近几年来还拥有了Mentor Graphics公司。 该公司的集成制造设计愿景关键是“闭环数字孪生”概念。上周Junko与Tony座谈时问到Tony：这到底意味着什么？
TONY HEMMELGARN: I guess the best way to define "digital twin" is, it's the linkage of what we define as the physical world to the virtual world. Why is that important? As products become more complex, the value of the digital twin is how closely we can represent that linkage between physical and virtual.
TONY HEMMELGARN: 我想 “数字孪生”的最好定义方法是，这是我们定义的物理世界与虚拟世界的联系。 为什么如此重要？ 随着产品变得越来越复杂，数字孪生的价值在于，我们可以多么接近地展现物理和虚拟之间的联系。
So for example, if you can represent the mechanical characteristics-- the software, the electronics, the electrical systems-- all of those are part of what makes a complex product. And so you can imagine, if you can only represent the mechanical characteristics, the value of the digital twin is only for the mechanical characteristics of the product. So the value is how much you can represent holistically of that product. And we use this for design, verification, validation, these types of things.
举例来说，如果你可以呈现机械特性——软件，电子设备，电气系统——所有这些都是制造复杂产品的一部分。 因此你可以想象一下，如果只呈现机械特性，则数字孪生的价值仅体现在产品的机械特性。价值的多少就是你可以整体体现该产品的多少。 我们将其用于设计，验证，确认这类型的产品。
But also, it's this concept of a closed loop digital twin. But what do we mean by "closed loop"? Closed loop says that we can gather information about what's happening with a product or a manufacturing process. Most industrial IoT solutions today will provide you information about preventive maintenance, condition monitoring, these types of things. But we want to know more. And the way we do that is, we leverage this digital twin.
而这就是闭环数字孪生的概念。 但是，“闭环”是什么意思呢？ 闭环表示我们可以收集有关产品或制造过程的信息。 如今，大多数IIoT解决方案会为你提供有关预防性维护，状态监控以及此类事件的信息。 不过我们想了解的更多。我们方式是利用数字孪生。
Now some say that if you throw enough data at the problem, you grab enough information through machine learning or artificial intelligence and so forth, you can solve any problem. The issue with that is, sometimes too much data can act like too little data. For example, I can show a direct linkage today between the number of people in the United States that had advanced degrees in Civil Engineering and the per capita consumption of mozzarella cheese. Two things that have nothing to do with each other. But with enough data, I can make it look like that.
现在有人说，如果你在问题上投入足够的数据，则可以通过机器学习或AI等手段获取到足够的信息，可以解决任何问题。 这样做的问题在于，有时过多的数据所起的作用反而会像数据太少的结果。 例如，现在我可以证明美国拥有土木工程专业学位的人数，与马苏里拉奶酪的人均消费量之间存在直接联系。 彼此无关的两件事，只是有了足够的数据，我便可以使他们看起来像是有联系。
So now think about complex products and complex manufacturing techniques. With enough data, how do I know I'm not making the same false correlations between engineering and cheese as I am between these types of things? So we feel like the best way to do this is to augment this process with a closed loop digital twin.
所以现在思考一下复杂的产品和复杂的制造技术。 一旦有了足够多的数据，我从何得知，处于类似这种事物之间的时候，没有犯我在工程师和奶酪之间关联的这种错误？ 因此我们认为，最好的方法是使用闭环数字孪生来巩固此分析过程。
So for example, if I've designed a product, I've run the analytics, I've done all the work, I know exactly how it's going to operate through my digital. But then I get it into usage and I'm finding out I've got a problem I did not anticipate. Maybe something's happening. Maybe it's an environmental issue. Maybe I'm in an area of the world that's very high humidity. And so I'm seeing some kind of a problem. Maybe I've got a vibration problem or something that's occurring. So I can take that data and I can bring it back to my digital model and try to understand what's happening. Because I have real-life data now, actual vibration data, that can feed back into my digital model and start playing what-if scenarios. What's happening with this thing? And so I can validate exactly where the core root of the problem may be coming from. Or even propose design changes based on what I'm finding, based on that model.
举例来说，如果我设计了产品，运行了分析程序，完成了所有工作，那么我确切地知道了它如何通过我的数字平台运作。但是后来当我开始使用它，发现我遇到了一个意想不到的问题，也许正有事在发生。也许是环境问题，也许因为我所处位置是世界上湿度很高的地区。或许我遇到了某种问题， 也许是遇到了振动问题，或是其它正在发生的事情。我可以由此获取这些数据，并将数据带回到我的数字模型中，尝试了解正在发生的事情。 因为我现在得到了真实的数据，就是实际的振动数据，这些数据可以反馈到我的数字模型中并开始模拟情景假设。这个问题是怎么回事？ 这样我就可以准确验证问题的根源可能来自哪里。甚至能够基于该模型，根据我的发现来提出设计修改。
The reason that's so important is, oftentimes with these IoT systems, they tell you have a problem, again, but they don't tell you why. And really, do I need IoT to tell me a machine's overheating? I've had that capability for many, many years. A red light goes off and says it's overheating.
JUNKO YOSHIDA: Or the experienced workers come in to see there's some anomalies on the factory floor.
JUNKO YOSHIDA: 或者经验丰富的工人进来看看工厂车间里有哪些异常情况。
TONY HEMMELGARN: And don't forget that experienced worker. I'll talk about that later, as to where this goes in the future, because I think it's a key, important aspect to this.
TONY HEMMELGARN: 而且，不要忘记那个经验丰富的工人。我将在稍后讨论这方面的发展，因为我认为这是关键、重要之处。
But again, I know I've got a problem, but I want to know why. I want to know why it's overheating. I don't just want you to tell me it's overheating. Preventive maintenance and condition monitoring. Those are very important things, and that's where most people will start with IoT solutions. But we feel like it has so much more to offer if you do the closed loop process.
不过再次讲，我知道我有问题，但我想知道的是问题出现的原因。 我想知道为什么会过热。 我不只是想让你告诉我它过热了。预防性维护和状态监视——这些都是非常重要的事情，这是大多数人开始着手IoT解决方案的地方。 但是我们觉得如果你能进行闭环处理，那系统能够提供更多的功能。
So that's for a product. But now think about a manufacturing process. It's no different. I can simulate the entire factory. I've designed the factory, I know the flow of the factory, I know everything about that factory and how it's going to operate and work. And if I start having issues, I can take those models and I can bring them back and I can simulate the factory. I could even, for example, simulate... Let's imagine I have a machine that goes down. It has a repair issue or whatever. I can simulate and rework the entire factory quickly to optimize based on a machine that I can't use anymore. And I can simulate that before I go back into the real-life production of that factory.
这是对于一个产品来说的。不过现在思考一下制造过程，也大同小异，我可以模拟整个工厂的运作。我设计了工厂，知道工厂的流程，知道关于工厂的一切，以及它的运作和工作方式。 如果工厂开始遇到问题，我可以采用这些模型，然后将数据代入模型，可以模拟工厂运作。 比方说我甚至可以模拟...让我们想象一下，我有一台机器故障了，它有维修方面或其他方面的问题。 我可以基于不再使用的机器，快速模拟和返工整个工厂来进行优化。在工厂回到实际生产之前，可以进行模拟。
So we think the closed loop process is extremely important. And this is the reason that, frankly, Siemens invested in software 11 years to bring this together, because we felt like it's one thing to have the automation equipment that runs the factory, but we also want to be able to simulate this in a digital world and be able to show exactly how all this comes together.
And this is why it's so valuable to our customers, because increasingly our customers are realizing that digital twin isn't a "nice to have" thing. It's becoming essentially. Because think about the complexity of products that are being built today.
JUNKO YOSHIDA: So many factors involved.
JUNKO YOSHIDA: 涉及到的因素很多。
TONY HEMMELGARN: So many factors. And if you think you're going to solve that by looking at a spreadsheet and looking at a list of issues, it's not realistic. And so with a digital backbone, I can now make those decisions much more confidently, much quicker. And we talk about complexity. Complexity's not going to go away in products.
TONY HEMMELGARN: 涉及很多因素。而且，如果你认为要通过查看电子表格并查看问题列表来解决该问题，那是不现实的。有了数字主干，我现在可以更加自信、更快地做出这些决定。我们谈论了复杂性。产品的复杂性永远不会消失。
Now some say you should try to limit complexity. We see it differently. We see it as the companies that are going to move faster, lower their production cost, increase their design capabilities faster than the other companies and also create new business models. Those are the ones that are going to use complexity as a competitive advantage. Because the more complex their products are, and the more able they're able to represent this in digital models, the faster they can go than their competition.
现在有人说，你应该尝试限制复杂性。 我们持有不同的看法。我们认为，与其他公司相比，这些重视复杂性的公司将可以更快地发展、更快地提高设计能力，降低生产成本，并且还可以创新业务模型。 这些都是将复杂性用作竞争优势的方法。 因为他们的产品越复杂，他们越有能力在数字模型中体现这一点，所以与竞争对手相比，他们发展得更快。
JUNKO YOSHIDA: Where do you feel you need to beef up to promote this idea of closed loop digital twin? Where do you go next?
JUNKO YOSHIDA: 你是从哪里感觉到，从而产生需要加强推广闭环数字孪生的想法？ 你的下一步计划是什么？
TONY HEMMELGARN: That's a great question. And now I link it back to what you said earlier. You commented about when the machine overheats, the person that knows kind of sometimes is the guy that's been running that machine for many, many years.
TONY HEMMELGARN: 这是一个很好的问题。 现在我回到你之前所说的问题。 你谈到，当机器过热的时候，那个已经运行了机器多年的人有时候正是发现问题的那个人。
So when we developed our IoT solution, MindSphere, one of the challenges we had is, How do we build enough applications to be able to leverage the value of the data that's coming in? Now, you can go to your traditional IT organization, and you got two problems there. One is, most of those IT organizations are way overloaded. They have so many things to work on, they'll never get to the apps that I need on my factory floor or whatever. The second issue is, the domain knowledge doesn't rest with them. It rests with the guy that's down at the machine.
因此当我们开发IoT解决方案MindSphere时，面临的挑战之一是，如何构建足够的应用程序以能够利用传入数据的价值？ 现在，你可以去看传统的IT组织，他们遇到两个问题。 一个是大多数IT组织都在超负荷运作，他们有很多的工作要做，他们永远都找不到我在工厂车间或任何其他地方所需要的应用程序。 第二个问题是，他们没有相关的领域知识。操作机器的那个人才具有领域知识。
And so, recently we acquired a company called Mendix. Mendix is a low code application software development tool. Low code means I don't have to be a software developer to write my applications. We put this software development into the hands of the domain knowledge users. So they can diagram the application the way they want it to be, and from that, they can develop applications very, very quickly.
And so we've taken it out of having to be a software developer to build the applications and put it in the hands of the people that actually have the domain knowledge to build these quickly. In fact, I'll share some examples of that this morning as well when we go through presentations. But the value of that is, is that it helps the IT organization because they've got enough to worry about right now, and it allows us to build applications that quickly can do this.
因此我们不必成为一名软件开发人员来构建应用程序，而是将其交到实际上具有领域知识的人们手中，以快速构建这些应用程序。 实际上，今天上午，在我们进行演示时，我也会分享一些案例。 这样做的价值在于，它可以为IT组织提供帮助，因为他们需要考虑的事情够多了，而且这个产品让我们能够构建，可以快速完成此项任务的应用程序。
Mendix had already been doing this for years. They've been around for 15 years. They're kind of still a startup, even after 15 years. But they focus mostly on business applications like HR, finance, these types of things. And they're very successful at doing this. We looked at it and said, Could we do that but also apply it to industrial applications? And so we're about nine months into this acquisition, and we're already seeing many, many examples of how to do this and bring this together.
Mendix已致力于这项工作多年，差不多15年了。 即使在15年后的今天，Mendix的规模仍然如同一家初创公司。Mendix主要关注人力资源、财务等这类业务应用上。 他们在做到这一点上非常成功。我们看了Mendix之后说，我们可以做到这一点，并将其应用于工业应用吗？ 距离此次收购大约有9个月的时间，而我们已经看到了许多如何做到这一点并将其整合在一起的示例。
And so our customers get excited, because they realize, Gosh, I could go very quickly now with this closed loop digital twin, because now I'm not dependent on even Siemens to build the applications. I can build them myself very quickly, and I use the solution that Siemens provides. With a combination of MindSphere, Mendix and our software solutions that we have today.
JUNKO YOSHIDA: Do you have any examples of people who have been successful in developing their own software using Mendix?
JUNKO YOSHIDA: 你有没有使用Mendix成功开发自己软件的公司案例？
TONY HEMMELGARN: Yeah, we do. We have... Well, I mean, some of them, again, they won't talk yet. But Mendix has many, many customers that have been successful on the business side. For example, again, Huawei is one of the customers that is using Mendix on the business side. And we're talking to those customers today about, How do you apply it to industrial? The industrial side. And you'll see more and more of that out from us over the next few months, where more and more, increasingly, customers will talk about this. Today, they're still early in this, but I can assure you they're very, very excited about this with what we're doing.
TONY HEMMELGARN: 是的，我们有的。我们有，不过，我的意思是，其中一些，他们暂时还不会透露。 但是Mendix有许多成功的商业客户。例如华为就是Mendix业务方面的客户之一。我们现在正与这些客户讨论，如何将其应用到工业领域？在接下来的几个月中，你会从我们这里看到越来越多的关于工业方面的消息，越来越多的客户将谈论这一点。 时至今日，他们仍处于起步阶段，但我可以向你保证，他们对我们正在做的事感到非常兴奋。
BRIAN SANTO: That correlation between college graduates and mozzarella consumption? Hemmelgarn called that "degrees to cheese." I love that.
BRIAN SANTO: 大学毕业生和消费马苏里拉奶酪之间的关系？ Hemmelgarn称其为“奶酪学位”。我喜欢这个称呼。
Synopsys chairman and co-CEO Aart de Geus was also at the Global CEO Summit. Synopsys is pursuing a similar strategy to the digital twin, which Synopsys more prosaically refers to as "virtual models." We have more about both Siemens and Synopsys in a story published on EETimes.com called, “From 5G to climate change and back again."
Synopsys董事长兼联席CEO Aart de Geus也出席了全球CEO峰会。Synopsys正在寻求一种与数字孪生类似的策略，Synopsys通常称之为“虚拟模型”。 EETimes.com上发布了一则故事，名为《从5G到气候变化再到5G》，文中有更多关于西门子和Synopsys的信息。
Yole Developpment is a French analysis firm that focuses on technologies whose roadmaps are not locked in to Moore’s Law. These are things such as power devices, sensors and microelectromechanical systems, or MEMS.
Jean-Christoph Eloy is president and CEO of Yole Developpment. Junko asked him what he sees as the most important trends in the coming years.
Jean-Christoph Eloy是Yole Developpment的董事长兼CEO。 Junko问Jean-Christoph Eloy，他认为未来几年最重要的趋势是什么。
JEAN-CHRISTOPH ELOY: Two that are important, one that for me is super important. One of the very important things is that the evolution of electric vehicles but also of the generation of energy by wind, solar and so on is driving the evolution of the power management, on power electronics. In order to have more compact modules to move from silicon to silicon carbide. And this is a very huge trend because it's changing the structure of the industry for power electronics and changing the way you're manufacturing the device. So moving out of silicon to move to silicon carbide. It's a very important trend.
JEAN-CHRISTOPH ELOY: 有两个趋势是很重要的，其中一个对我来说极其重要。 对我极其重要的是电动汽车的发展，以及风能、太阳能等能源的产生，正在推动电力电子技术中电源管理的发展。硅转到碳化硅，模块更紧凑。这是一个非常大的趋势，因为它正在改变电力电子行业的结构，并改变你制造设备的方式。 因此，从硅转到碳化硅，这是非常重要的趋势。
Another trend is that you need sensors for everything. Sensors for the IoT, sensors for the artificial intelligence (because you need data to do artificial intelligence), you need sensors for ADAS, for the cars, for autonomous vehicles, and so on and so on. So sensors are moving step by step to any product. I think a mobile phone has 22 sensors. It's huge. And in cars, it's more than that. So sensors are really moving everywhere.
But these are trends that are already well established for a long time, so it's increasing at the moment, but it's something that started really 15, 20 years ago.
One of the key evolutions that we see at the moment is having the technology to shape and structure light and manage light. What was done in a shoebox or in rooms 10 years, 20... the big optical systems. Now you are able to... manufacturers integrate them in less than one cubic centimeter. And it's a convergence of image sensors. It's a convergence of optics management with lenses, micromirrors and so on. And light emission with vexils.
And all these technologies were both bulky and expensive, and now it's starting to be very well integrated. And the first products showing this integration like 3D sensing in mobile phones, but also very compact lidar, gas sensors, are step by step happening on the market and leveraging 25 years of development of light management technologies to move from a very bulky system to very tiny and cheap technologies. And it's a key movement and which shapes tens of billions of new business, and which is really the convergence between silicon optics, light management and coming from micro-mechanics, coming from pure sensing and also coming from the LED and vexil business.
JUNKO YOSHIDA: So that's really the convergence of a lot of things that had happened independently until now. Can you tell me who are actually leading in that big trend towards the integration of light systems and imaging and optics and all that?
JUNKO YOSHIDA: 这实际上是到目前为止发生的许多独立器件的融合。能否请你告诉我，是谁在真正引领着集成光系统、成像和光学等所有这些东西？
JEAN-CHRISTOPH ELOY: What's interesting is that we have companies that are coming from different parts of this industry. For example, you have companies that are coming from more of the camera module, so the integration. It's companies like LG, for example. You have companies that are coming from the sensing part like Sony, which is really the world leader for image sensors. You have companies that are coming more from the driving side like AMS, that has made multiple acquisitions in order to move from driver to light chipping to image sensors. You have companies like STMicro, that is also coming from more the image sensor business.
JEAN-CHRISTOPH ELOY: 有趣的是，我们这行业拥有来自不同领域的各个公司。 例如。比方说，有来自侧重于摄像头模块方向的，做集成的。 例如像LG这样的公司。 也有像索尼这样来自传感领域的，索尼确实是全球图像传感器的领头羊。有像AMS这样做驱动的公司，AMS已经进行了多次收购，以便从驱动转到照明芯片再到图像传感器。 有像ST这样的公司，也侧重于图像传感器业务。
So you have four or five companies that are really leading the way, coming from different parts of the industry, but are in the same focusing. Now you are really able to structure modules with light generations, optics, light chipping and detections in a very compact module.
JUNKO YOSHIDA: Tell me more about the application of that. We talked about lidar, we talked about 3D sensing in smartphones. How would that change our lives in terms of the applications?
JUNKO YOSHIDA: 请再多讲讲关于该应用程序的信息。我们谈论了激光雷达，谈论了智能手机中的3D感应。从应用角度，这将怎样改变我们的生活？
JEAN-CHRISTOPH ELOY: Well, it's mainly integration of new functions that were not available for consumer or automotive applications. So lidar is something that is already a very big market, but not for automotive. And so the ability to integrate, lower the costs and keep the accuracy is very key. And this is what these technologies are enabling. 3D sensing in the same way. Face recognition was a high-end security feature, which is now in phones. And this is really the ability of these technologies to address.
JEAN-CHRISTOPH ELOY: 好的，它主要是集成新功能，而这些新功能不适用于消费类或汽车应用。激光雷达已经是一个很大的市场，但不是用于汽车的。所以进行集成、降低成本和保持准确性的能力是非常关键的。而这正是这些技术所带来的。3D传感也是同理。人脸识别是一种高端安全功能，目前已在手机中使用。这确实是这些技术解决问题的能力。
But there are other things that are developing. For example, microphones are very important for many products. But the problem with microphones, which is very important, is that to have a microphone you need an interface with the external world to get the sound. To have that kind of technology that could be able to work in those environments where you have water and so on is very complex. And optical microphones are coming on in order to be able to do that. Optical microphones.
但还有其他事物也正在发展。例如，麦克风对于许多产品非常重要。 但是对于麦克风来说有个问题至关重要，那就是，即使拥有麦克风，你也需要与外界有接口才能获得声音。能够在水中等环境里工作的麦克风，其涉及的技术是非常复杂的。 为了能够在这类环境中使用，光学麦克风正在问世。 光学麦克风。
So you have those kinds of things that are emerging, which will not be totally visible from the user, but it's changing the structure of the device in order to enable it to work in a lot of different environments for the microphones, or integrate functions that were not accessible for consumer applications up to now.
And there is also an impact, for example, of this technology more for high-end functions. Optical integration is also optical interconnections. It's moving to silicon photonic. And it's pushing the optic interconnections from the fiber optics that are between two continents to something that is getting closer to data center, to inside data center and inside the data center, inside the rack. And step by step the light is moving up to the silicon chip. So it will take 10 or 15 years to move into the silicon chip, but this is the movement. And it's enabling by these technologies of integration of light generation, light chipping and detection.
这种技术对高端功能的影响也更大。光学集成也是光学互连，目前正转向硅光子。 该技术将光互连从原来的，远如两大洲之隔的光纤推向彼此越来越靠近的数据中心，进入数据中心内部，到数据中心内部、机架内部的地方。光技术逐步转向硅芯片。进入到硅芯片需要10到15年的时间，不过这就是发展的方向。 这些技术使得光产生、光碎裂和检测能够集成在一起。
BRIAN SANTO: Sensor technology is fundamentally passive, in that sensors react to some phenomenon: light, sound, motion. But the technology has taken some leaps in recent years. Radars, lidars, 3D mapping techniques. They all make it possible to not just detect things, but to identify what’s in the environment.
BRIAN SANTO: 传感器技术从根本上来说是被动地在发展，依赖于对某些现象如：光，声音，运动做出反应来发展。近年来，这项技术取得了一些飞跃性的成果。雷达，激光雷达，3D映射技术。 它们不仅使发现事物成为可能，还使识别环境中的事物成为可能。
Pierre LaBoisse is Executive Vice President of Global Sales at AMS. I asked him about this transformation in sensor technology and what practical applications there might be.
Pierre LaBoisse是AMS全球销售执行副总裁。 我询问了他，关于传感器技术的这种转变，以及有什么实际应用可能应运而生。
PIERRE LABOISSE: I would go back into the car to illustrate and onto the question. The 3D in the car will help to identify and also create safety I would say around the passengers, the drivers and everything which is in the car. So in that case, it's way beyond detecting. It's sensing and anticipating. And the way you do it, you do it with 3D in the car, you also do it with multiple sensors that you have from your seat to your steering wheel. So it's really sensing to anticipate.
PIERRE LABOISSE: 我将回到汽车这个话题上来解释问题。我想说的是，汽车中的3D可以帮助识别并创造安全性，围绕乘客、驾驶员和汽车中所有物体的安全性。 因此在这种情况下，传感器所具备的远不止是检测功能，而是感知和预测。并且在汽车中使用3D进行处理时，还需要使用从座椅到方向盘的多个传感器进行协作。 所以它真的是从感知到预测。
If you take the example in the health care segment, there you do not detect. There again, you anticipate to be able to measure some critical vital tone, as an example. Your heartbeat monitoring. And this is not detecting. Detecting was when the beginning of the sensor where it was more mechanical I would say. It's becoming way more digital today, and that goes to the evolution from ICs to solutions, to what you can do in fusion, by the way.
如果用该技术在医疗保健方面的表现作为示例来看，它能监测你不监测的。 例如，你期望能够测量一些重要的生命指标，如监测心跳。我要说的是，监测是从传感器开始更机械化的时候。 如今它正变得越来越数字化，顺便一提，从集成电路到解决方案，再到融合你可以做的东西。
BRIAN SANTO: I asked Pierre to tell us more about sensor fusion.
BRIAN SANTO: 我请Pierre告诉我们更多有关传感器融合的信息。
PIERRE LABOISSE: Sensor fusion is a direction that a lot of companies would take, I would say. And the objective is also how do you save and gain power in ways that you can see. And as I just said, how you combine different capabilities out of sensors IC. To be able to merge fusion, once again, and support multiple types of applications.
PIERRE LABOISSE: 我想说，传感器融合是许多公司会选择的发展方向。 目标也是如何以可见的方式节省和获得能量。正如我刚才所说，如何将传感器IC中的不同功能组合在一起。以便能够再次融合，并支持多种类型的应用。
So you could imagine in the near future a sensor fusion to serve multiple ports. Whereas today, sensor or sensor ICs could be on the binary serving one principle or one application or one whatever. So that's really the evolution it takes.
BRIAN SANTO: That was Pierre LaBoisse of sensor specialist AMS.
BRIAN SANTO: 以上是传感器专家AMS的Pierre LaBoisse的发言。
So that wraps our interviews from the Global CEO Summit in Shenzhen. As I said, the subject matter was all over the technological map.
That said, there was an over-arching theme. Everyone in the industry is trying to find ways to make sense of the escalating flood of data.
After listening to the speakers at last week’s Global CEO Summit, it seems there’s been a subtle change in focus. We’ve gone beyond simply trying to create a sensor-rich environment and are now trying to figure out how to analyze sensor data locally so that it’s actionable. Enabling AI is no longer enough; now the concern is using it efficiently to render useful results. 5G is no longer about just adding capacity; now it’s about enabling new applications.
在听了上周的全球CEO峰会上演讲嘉宾的发言之后，似乎大家的侧重点已经发生了微妙的变化。 我们不仅仅是尝试创建一个传感器丰富的环境，同时也试图弄明白如何在本地分析传感器数据，以使其可运行。只启用AI已不能满足需求。现在的关注点是有效地使用AI来提供有用的结果。 5G不再单单意味着增加容量，现在成为赋能新应用的保证。
In a keynote that opened the Global CEO Summit, Wei Shaoujun, the president of the IC design branch of the China Semiconductor Industry Association, said, “5G is not just mobile communications. This will affect the entire infrastructure of the nation.”
That wraps our Weekly Briefing for the week ending November 15th.
This podcast is Produced by AspenCore Studio. It was Engineered by Taylor Marvin and Greg McRae at Coupe Studios. The Segment Producer was Kaitie Huss.
该播客由AspenCore Studio制作。Coupe Studios的Taylor Marvin和Greg McRae担任设计。Kaitie Huss担任片段制作人。
The transcript of this podcast can be found on EETimes.com, complete with links to the articles we refer to, along with photos and video. We’ll be back next Friday with a new edition of EE Times on Air. I’m Brian Santo.
EETimes.com上有本播客音频的文字版本，包含我们所引用文章的链接、照片和视频。 我们将在下周五播出新一期的EE Times on air。 我是Brian Santo。