3月25日，在亚洲青年领袖论坛高质量发展主题论坛平行对话中，Red Fields公司联合创始人索尼·巴迪加发表了自己的观点，摘录如下。
结合“工业4.0”谈对高质量发展的深度理解
可以说，我们正在经历第四代工业革命。第一代工业革命大概是1760年到1840年，那时出现了机械化，标志着自动化开始了。第二代工业革命大概是生产的规模化，从19世纪60年代到1914年第一次世界大战时期。然后到了下一代，也就是第三代——计算机革命，带来了计算机，时间大概是20世纪60年代到2000年。
现在，我们正在经历第四代工业革命，也就是人们所说的“工业4.0”。“工业4.0”是制造、硬件系统、物联网、人工智能、机器学习、增强现实、云计算等的集合。也就是说，我们现在已经进入了一个新的世界。在这个世界里，所有的系统互联互通，可以给出实时反馈。这样的话，在运行相关流程时，可以得到即时反馈，能够在事发前预见到机器会发生的故障。这会改变整个局面：创新在增加，生产力在增加，故障在减少，浪费在减少，人力也在减少。这是我理解的高质量发展。
以一名资深投资人的角度谈高新企业和初创企业未来的投资机遇
我认为，大家寻求高质量发展是不可避免的，原因是世界也在朝着这个方向前进。如果你在运营一个制造项目，你需要将里面的大数据、制造系统以及人工智能、机器学习、云计算等全部串联起来。如果做不到，你和其他正在朝这个方向转变的企业相比就处在显著劣势。如果你可以提前预见到机器故障，你就可以优化你的产品，优化响应时间。以前，决定是在中央层面做出来的。现在，有了实时数据和反馈之后，你能自主做出决定，系统能自主做出决定，就能减少循环时间。
如果企业不采用这种方式，企业的成本结构会改变，企业会变得非常不具备竞争力。因此，我认为需要启动这种转变了。我们现在正在经历我所称的“制造业的数字化转型”，其中的所有系统互联互通，而这些系统在以前是相互独立的，彼此不通信息。现在，我们将价值链和产业链所有环节的系统和信息连接起来。例如博世，它在无锡有个不错的工厂，已经实施了工业4.0，并且是在四五年前就已经实施了。显然，现在达成了15%～20%的成本结构减少。
谈未来创新发展最大的挑战
以前，必要性是发明创造之母。但现在，情况似乎反过来了。例如，当乔布斯发明iPhone的时候，我们并不知道我们需要它。现在，很多的创新，比如字节跳动的抖音做的短视频，在推出前我们也不知道我们需要它。因此，我们似乎正朝着相反的方向前进——从渐变式创新转变到剧变式创新，我们开始接触到一些以前从未设想过会存在的事物。
我观察到一种现象：在中国，在一项创新发生的时候，目的并不是为了拥有一个完美的产品，而是为了尽快占领市场，这成为了一个激进的入市行为，然后产品才逐渐进化成为顶尖产品，这和其他市场的情况有些不同。在其他市场里，人们会先花时间打磨一款完美的产品然后才推向市场。我认为，世界上其他区域也在逐渐向中国这种模式靠拢，人们愿意做一点妥协，尽早向市场推出产品。这是我观察到的一个方面。
我也想花时间谈一谈这类创新的负面影响。当万物互联了，就要考虑数据和隐私的问题，也要考虑潜在的失业问题。这是两个大问题，我认为刚刚也有嘉宾谈到过。当世界机械化以后，人们产生了担忧，但人们会找到事情可做。人工智能、机器学习或者其他事物，最后可能也是高质量的问题。
Sonny Badiga says innovation is the core engine of corporate development in Industry 4.0
On 25 March, Sonny Badiga, co-founder of Red Fields, shared his thoughts at the High-quality Development Forum of the Asia Youth Leaders Forum. Following is an excerpt from his speech.
Question: When you hear the word “high-quality development”, what comes to your mind?
I’d say we’re going through the fourth generation of the industrial revolution right now. The first generation was probably back from 1760 to 1840, when we had mechanization where automation started. And then we went through the second generation, which was probably mass production from – call it – 1860s to the first World War in 1914. And then we went through the next generation, the third generation, which was computer revolution where computers came in; that was probably from 1960s to 2000.
And now we’re going through the fourth generation, which everybody calls “Industry 4.0”. So, industry 4.0 is the confluence of bringing in manufacturing, physical systems, along with the IoT (internet of things), AI/ML, augmented reality, cloud computing, and so on. So now we’ve sort of arrived in a world where all the systems are interconnected so that you get real-time feedback. So you can operate your processes, get more instantaneous feedbacks, and identify breakdown before the machines actually do break down. It sort of changes the whole dynamic where you are increasing innovation, you are increasing productivity, you are reducing breakdown time, you are reducing wastages, and you are also reducing a lot of human requirements. So that’s sort of what this means to me.
Question: What do you think when talking about high-quality development, especially in high-end manufacturing and highly innovation-driven entrepreneurs and startups? How do you see the future trend for investment opportunities as a senior investor?
What I would say to that is I think it’s inevitable that people have to go down this path because the world is moving in that direction. In case you have manufacturing operation, you need to have your operation to be fully connected between big data, your manufacturing systems, and all the things that Aaron and this guy is doing – AI/ML, cloud computing, and so on. Because if not, you would be at a significant disadvantage to the other businesses that are moving to that direction. Because you can predict a breakdown of the machine before it happens, you can improve the quality of your product, and you can improve the reaction time. Previously, decisions were being made at a centralized level. Now with instantaneous data and feedback, you will be able to make autonomous decisions; the system itself will make autonomous decisions, whereby you can reduce your cycle time. So, in the event companies don’t go down this path, their cost structure will change, and they will become very, very uncompetitive. So, I think it's a journey to start. So, we’re sort of going through what I call “manufacturing digital transformation” whereby systems are connected whereas before they were separate systems that do not communicate with each other. So now we’re connecting systems and data all across the value and supply chain. Looking at Bosch, these guys, in Wuxi they have a decent factory. They have sort of also implemented Industry 4.0. And apparently this was even 4 or 5 years ago that they’ve done this. Apparently, they have 15-20 percent of reduction of cost structure.
Question: When talking about innovation in the future, what do you think is the biggest challenge?
I’d say, you know, in the past, necessity was always the mother of all invention. But I think we sort of come full circle from that. For example, when Steve Jobs did the iPhone, none of us even knew that we needed that. So a lot of innovation, like when Douyin (Bytedance) did those short videos, we never thought we needed that. So we sort of come full circle from doing step-by-step incremental innovation to sort of what I call transformational innovation where we’re sort of being exposed to things that we never even imagine were possible.
One of the observations that I would make is that I’ve seen in China, for example, when the innovation journey started, initially, it was not about having the perfect product, but actually scaling out the market as quickly as you could. So that becomes a daring entry, and then the product evolves to become state of the art, which is a little different than other markets where they first spent all the time perfecting the product, and then they came into the market. So I think the rest of the world is also moving a little bit to that model whereby they are willing to sacrifice to go to market and introduce their product early, so that’s one aspect I’m seeing.
I also spend maybe a second to talk about the downsides of this because by having everything interconnected, you do have data and privacy issues, and then you also have potential job losses. Those are two big issues, but then I think one of the panelists addressed that. It’s like when the world mechanizes, people are worried about that, but then people will go and find things to do. And the AI, or ML, or so on, it might be a high-quality problem at the end of the day.
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