[00:00:11] Tom Garrison: Hi, and welcome to this special episode of InTechnology. I’m your host, Tom Garrison, and I’m joined by my co-host Camille Morhardt. And Camille, this week is a special week. It’s Thanksgiving and obviously we celebrate that here in the US. And so, we thought it’d be a great time to show our thanks to the listeners.
[00:00:33] Camille Morhardt: And we always want to hear from people what topics they’re interested in hearing more about and different perspectives on. And of course, we also look always at what’s getting the most downloads and what kinds of things people want to hear about. So we thought it’d be interesting for this episode, as a treat for the listeners, to actually play back what they liked best. So this is some of the most popular episodes that we’ve had this year.
[00:00:59] Tom Garrison: That’s right. And now, so drum roll please. What were the most popular episodes and topics? And these are in no particular order for those of you keeping track at home. First is cloud computing. Second is artificial intelligence. Third is sustainability. And the last one we’ll cover today is machine consciousness.
So let’s get to the first episode, and again, these aren’t in any particular order. But back in June, we had a show focused on cloud security. And it doesn’t surprise me that this was a popular one. It was really, really interesting and it’s really because when you think about it, so much has changed in the last few years when it comes to cloud computing.
[00:01:45] Camille Morhardt: Yeah, I mean we were already experiencing a shift to software as a service based apps prior to the pandemic, and that, obviously, the pandemic then accelerated that transition. We’ve also seen in the news over the year some high profile outages at cloud providers, all this driving extra interest and knowledge among all sorts of people about the cloud and wanting to know more.
[00:02:13] Tom Garrison: That’s right. And historically, companies, large enterprises and whatnot, when they have chosen a cloud provider, they have chosen a single cloud provider. And when you start thinking about things like extreme weather events or earthquakes or other issues that shut down a single provider, that puts people out of luck when that provider isn’t available.
And so, we thought it would be a good idea to talk to someone about the current state of cloud storage and security.
[00:02:44] Camille Morhardt: We spoke with Jo Peterson, she’s Vice President of Cloud and Security at Clarify360, and she told us that cloud customers are starting to rethink having all their eggs in one cloud basket, as she put it.
[00:03:00] Jo Peterson: It’s really important to talk about resiliency. Are you housing workloads across multiple availability zones? Are you supporting region routing using things like domain name services? Are you backing up your data? Are you encrypting that data? And we talked to them about some basic hygiene things that you should be doing. Have you secured your user endpoints? That translates into all endpoints. You might have the users squared away, but maybe you don’t have your VM squared away; maybe you don’t have your server squared away.
Let’s think about things like the shared responsibility model, because the shared responsibility model is different for each cloud provider and it’s different for each product within that cloud provider. So, are you and your team sure about what your responsibility is, as it relates to that cloud provider and that particular product? And it gets even crazier when you’re dealing with multiple clouds. It’s a lot for anybody to remember. We tell them, “Hey, look at your cloud usage policies. And I know it seems super simple, but practice good password hygiene.” Who’s got the passwords to this stuff? So, doing everything to ensure that workload’s protected along its journey as much as possible.
[00:04:26] Camille Morhardt: Jo Peterson is Vice President of Cloud and Security at Clarify360.
[00:04:37] Tom Garrison: Another popular episode this year focused on IOT devices and, in particular, how these devices and systems can affect a business’s approach to cybersecurity. And interestingly enough, that’s actually an issue we’ve been studying at Intel along with a team at Epiphany Systems. They’re a company focused on proactively identifying cybersecurity gaps.
[00:04:59] Camille Morhardt: So we invited Malcolm Harkins, who’s the company’s Chief Security and Trust Officer, along with Rob Bathhurst, who’s the company’s co-founder and CTO to talk about how IOT devices are changing the way companies need to look at cyber security in the workplace.
[00:05:17] Rob Bathhurst: So, if you look at a building, most people just think of it as a shell with glass and doors and floors. And really, when you look at it, it really is a connection of different systems. In most modern buildings, because of energy regulation, they put in automated control systems for their furnaces, their boilers, they’re air conditioning units, elevators, power systems, access control.
It’s all connected. And it’s all sitting on this network that is not really thought about the same way that you might inside a corporation. And so they usually just connect it together, together and make it work and hope for the best, and a lot of the realization has come around to how do they secure it.
[00:06:04] Malcolm Harkins: In some cases it might be easier for an attacker to, in essence, attack and exploit the building and create that ransomware event, rather than just all the PCs and the servers and that type of stuff. The facilities’ systems that manage those buildings have, by and large, been built and managed separately from the traditional IT environment.
Now, there’s the traditional perspective of the perimeter. Makes a lot of sense, we always have to harden that as much as possible and that perimeter could be at the device, at the data level and the network level, all those type of things.
But that’s an intact surface view of things that perimeter and it doesn’t really get to the depth of the connectivity between devices, applications, identities, and networks. It’s really about starting from the inside out, not the outside in.
[00:07:03] Rob Bathhurst: Just to tail onto that, if I may. In the security industry, we have a bad habit of saying well, my responsibility is this and so this is where I’m going to stop thinking about the problem. And what you really need to take into account is the interconnected nature of the system. And actually, if you come together as a team and discuss how bad it could be and what the attacker’s objective might be, you get a much better overall defensive understanding that way than you would typically.
If we look at the security industry right now, we basically hire former arsonists to come try and burn our building down and then tell us whether or not they were able to light it on fire. But in reality, when you build the building, you have a building inspector. You have a fire marshal. You have people come around and check it and evaluate it and make sure it’s up to code. And we don’t have that same rigidity in the security space. And so, we really need to get out of the calling the fire department as our first reaction for security or hiring an arsonist is our first reaction for security, and get more to the proactive inspection side of it.
[00:08:19] Camille Morhardt: We just heard from Rob Bathhurst, co-founder and CTO of Epiphany Systems. And with him, the company’s Chief Security and Trust Officer, Malcolm Harkins.
[00:08:38] Tom Garrison: Well, from the cloud to IOT and now sustainability, we recently made a shift to a new podcast name InTechnology, but we also added sustainability to our mix of topics.
[00:08:51] Camille Morhardt: Now we’re covering everything from zero trust to net zero.
[00:08:55] Tom Garrison: That’s true. That’s true. And it makes a lot of sense why we added sustainability. When you think about companies that are obviously trying to do the right thing, from being a good world and corporate citizen, but also they’re looking at their bottom lines and saying how can we do business in a more sustainable long-term fashion? But how do I use technology to lower my cost, to lower my carbon footprint? All of these aspects blend together in a lot of really interesting ways.
[00:09:26] Camille Morhardt: Right. Technology, in large part, is what’s going to be able to drive improvements in sustainability. And of course, if we’re using technology to do that along with our critical infrastructure, it better well be secure.
So, we’ve just finding they continue to intersect more and more and more. It’s explicit now, it’s part of it. So one of our first InTechnology conversations was with Tamar Eilam, who’s an IBM Fellow and also Chief Scientist there for sustainable compute.
And she has an interesting story, because she spent years working in cloud computing, but then she heard a lecture on sustainability and it really lit a fire under her. And she has made the shift to completely focus on sustainability and compute at this point.
[00:10:14] Tom Garrison: Yeah, and she shared with us some pretty significant trends that show why this work is so important.
[00:10:21] Tamar Eilam: Really, we are at an inflection point where there are multiple trends that are obvious and that are happening today. And one is the exponential data and data transfer. Everything is on Zoom and all these video transfer games and so on. So that’s obvious and that, of course, comes with energy emission and so on.
Then there is the new emerging workloads in the cloud that are very energy hungry, such as AI. So if you look just at AI, which is obviously very popular for very good reasons, the energy for training AI jobs doubles every three to four months.
[00:11:07] Tom Garrison: Wow.
[00:11:09] Tamar Eilam: That’s crazy. And AI… Look, AI’s an amazing tool. We in IBM are all embracing AI. We’re doing AI. We’re living AI. And that’s because AI can help us actually really face all of these challenges including discovery of material for carbon capture. Including analyzing satellite images and predicting climatic events. AI is a great tool. However, with power comes responsibility, as I like to say. So how can we use AI responsibly and how can we really work to make AI more efficient? That’s the second trend.
And then the third trend has to do with the demise of Dennard scaling, also known as the flattening of Moore’s Law. And basically what that says is that we cannot continue to expect to get the efficiency improvements from general purpose computing chips, like we used to get every two years. You get more energy efficient and more energy efficient and more energy efficient. And that’s because we reached the limits of physics. And that’s why there is a move to specialize systems. But because of these three trends, this has caused some to raise the alarm on the increasing energy consumption of computing in general. In fact, the semiconductor corporation published a report, the CATO report, and basically the bottom line there is the energy for computing overall is growing in a faster rate than the energy that we’re producing, period. Than the power they’re producing, period. And that’s a problem, because obviously we need more computing, but we need more efficient computing.
[00:12:59] Camille Morhardt: That was Tamar Eilam, IBM Fellow.
[00:13:02] Tom Garrison: And Camille, Tamar used the word “alarm” there and I think with good reason. But she’s also shared some bright spots of approaches that can get us moving forward toward sustainable computing. For example, going back to the cloud, people are looking at ways to leverage times when there’s more predictable renewable energy powering the grid.
[00:13:22] Camille Morhardt: Yeah, and I thought it was interesting, because even though we consider energy output when it comes to using technology, Tamar still believes technology is the answer to solving a lot of these problems in the climate space. So, she’s proposing if we can get more efficient algorithms and artificial intelligence that are less processing intensive and run those where and when there’s renewable power, we can even moderate energy usage.
[00:13:51] Tom Garrison: It’s very clear. We’ve only scratched the surface on sustainability this year and we have a lot more episodes on the topic coming up next year, so stay tuned.
Well, our final listener favorite for this special Thanksgiving thank our listeners episode, is the conversation you had, Camille, on what that means looking at machine consciousness.
[00:14:22] Camille Morhardt: Yeah. Well, back in June, there was a bunch of stuff in the press about an engineer at Google who had claimed that the AI chat bot that he was working on had actually become sentient or come to life or now had machine consciousness. So I thought, well, what does that mean? So actually chatted with Joscha Bach, who is a principal researcher in Intel Labs here. And he is a computer scientist, but he’s also a philosopher, and he really walked through a whole bunch of different concepts, including the difference between sentience and consciousness and what really constitutes even a machine and what different things can go together in that space.
[00:15:12] Tom Garrison: I found this to be absolutely fascinating. And in fact, it’s not uncommon for me to listen even if we record it together. This one was just you, Camille, but even when we record it together, I might listen to an episode just because you get a different perspective than when you’re actually recording.
But in this case, I listened to this one twice. To me, it asked a pretty foundational question and an important one, which is how would you know if in fact we have created an entity? It’s something that has consciousness, that has become sentient. That to me is a very perplexing question, and one that’s very, very difficult to answer. It’s very easy to ask, but difficult to answer. But this is a great first step.
[00:16:02] Camille Morhardt: To me, it feels pretty clear cut today, just on a personal level, but as we start to see greater and greater convergence between biology and technology, I think that that line is going to appear more and more blurred, so it’s important to start thinking about it now.
[00:16:19] Joscha Bach: The way I use sentience is that it describes the ability of a system to model its environment and it discovers itself and its environment and the relationship that it has to its environment, which means it now has a model of the world and the interface between self and world. And this experience of this interface between self and world, but the world that you experience is not the physical world. It’s a game engine that is entrained in your brain. Your brain discovers how to make a game engine like Minecraft, and that runs on your neocortex and it’s tuned to your sensory data. So, your eyes and your skin and so on are sampling bits from the environment and the game engine in your mind is updated to track the changes in those bits and to predict them optimally well. To say, when I’m going to look in these directions, these are the bits that I’m going to sample and my game engine predicts them.
This is how we operate it. In that game engine, there is an agent. And it’s the agent that is using the contents of that control model to control its own behavior. And this is how we discover our first person perspective. The self, right? That is the agent that is me, that is using my model to inform its behavior. And inside of this agent, we have two aspects. One is perception. That’s basically all these neural networks that are similar to what deep learning does right now for the most part. And that translates the patterns into some kind of geometric model of reality that tracks reality dynamically.
And then you have reflection. That’s a decoupled agent that is not working in the same timeframe, and that can also work when you close your eyes and that is reflecting on what you are observing. And that thing is directing your attention. And this is this thing that is consciousness. Difference between consciousness and sentience in this framework is that sentience does not necessarily require phenomenal experience. It’s the knowledge of what you’re doing. So in this perspective, you could say that, for instance, a corporation like Intel could be sentient. Intel could understand what it’s doing in the world. It understands its environment. It understands its own legal, organizational, technical cores and structure, and it uses people in various roles to facilitate this understanding and decision-making.
But Intel is not conscious. Intel, it does not have an experience of what it’s like to be Intel. I think that, practically, consciousness comes down to the question of whether a system is acting on a model of its own self-awareness. So is this model aware that it’s the observer and does this factor into its behavior? This is how you can recognize that a cat is conscious, because the cat is observing itself as conscious. The cat knows that it’s conscious and it’s communicating this to you. And you can reach an agreement about the fact that you mutually observe each other’s consciousness. And I suspect that this can also happen with the machine, but the difficulty is that the machine can also deep fake it.
[00:19:11] Camille Morhardt: Mm-hmm. Mm-hmm.
[00:19:12] Joscha Bach: And deep faking it can be extremely complicated. So, I suspect that for instance, the LaMDA bot is deep faking consciousness and you can see the cracks and this deep fake. For instance, when it describes that it can meditate and sit down in its meditation and take in its environment and you notice it has no environment, because it has no perception. Cannot access the camera.
There is nothing what it’s like to be in its environment, because the only environment that it has is inside of its own models, and these models do not pertain to a real-time reality. So when it pretends to have that, it’s just lying.
[00:19:46] Camille Morhardt: Right.
[00:19:46] Joscha Bach: It’s not even lying, because it doesn’t know the difference between lying and saying the truth because it has no access to that brown truth.
[00:19:54] Camille Morhardt: That was an excerpt from my conversation with Joscha Bach, a principal researcher in Intel Labs who’s focused on artificial intelligence, if you didn’t gather that by now. I encourage you to listen to the entire episode. Some people have even done it twice.
[00:20:10] Tom Garrison: That’s true.
[00:20:11] Camille Morhardt: We’ll put the links to all four of our listener favorites in the show notes, so it’s easy for you to find them.
[00:20:16] Tom Garrison: Yeah. And listeners, I hope you enjoyed this Thanksgiving look-back at your favorite episodes from this past year. Camille and I really appreciate your continued support, and we’re always open to your suggestions for topics and guests, so keep them coming.
The views and opinions expressed are those of the guests and author, and do not necessarily reflect the official policy or position of Intel Corporation.
