Tag Archives for " Technolgy "
The Modern Data Warehouse – Enterprise Data Curation for the Artificial Intelligence Future
This free 1-hour webinar from GigaOm Research brings experts in AI and data analytics, featuring GigaOm analyst William McKnight and a special guest from Microsoft.
The discussion will focus on the promise AI holds for organizations in every industry and every size, and how to overcome some of the challenges today of how to prepare for AI in the organization, and how to plan AI applications.
The foundation for AI is data.
You must have enough data to analyze to build models.
Your data determines the depth of AI you can achieve — for example, statistical modeling, machine learning, or deep learning — and its accuracy.
The increased availability of data is the single biggest contributor to the uptake in AI where it is thriving. Indeed, data’s highest use in the organization soon will be training algorithms.
AI is providing a powerful foundation for impending competitive advantage and business disruption.
In this 1-hour webinar, you will discover:
- AI’s impending effect on the world
- Data’s new highest use: training AI algorithms
- Know & change behavior
- Data collection
- Corporate Skill Requirements
You’ll learn how organizations need to be thinking about AI and the data for AI.
Register now to join GigaOm and Microsoft for this free expert webinar.
Who Should Attend:
- CIOs
- CTOs
- CDOs
- Business Analysts
- Data Analysts
- Data Engineers
- Data Scientists
Source: gigaom.com
Voices in AI – Episode 63: A Conversation with Hillery Hunter
About this Episode
Episode 63 of Voices in AI features host Byron Reese and Hillery Hunter discuss AI, deep learning, power efficiency, and understanding the complexity of what AI does with the data it is fed.
Hillery Hunter is an IBM Fellow and holds an MS and a Ph.D. in electrical engineering from the University of Illinois Urbana-Champaign.
Visit www.VoicesinAI.com to listen to this one-hour podcast or read the full transcript.
Transcript Excerpt
Byron Reese: This is Voices in AI brought to you by GigaOm, I’m Byron Reese. Today, our guest is Hillery Hunter. She is an IBM Fellow, and she holds an MS and a Ph.D. in electrical engineering from the University of Illinois Urbana-Champaign. Welcome to the show, Hillery.
Thank you it’s such a pleasure to be here today, looking forward to this discussion, Byron.
Q: 1
So, I always like to start off with my Rorschach test question, which is: what is artificial intelligence, and why is it artificial?
You know that’s a great question. My background is in hardware and in systems and in the actual compute substrate for AI.
So one of the things I like to do is sort of demystifying what AI is.
There are certainly a lot of definitions out there, but I like to take people to the math that’s actually happening in the background.
So when we talk about AI today, especially in the popular press and such and people talk about the things that AI is doing, be it understanding medical stands or labeling people’s pictures on a social media platform, or understanding speech or translating language, all those things that are considered core functions of AI today are actually deep learning, which means using many-layered neural networks to solve a problem.
There are also other parts of AI though, that is much less discussed in the popular press, which includes knowledge and reasoning and creativity and all these other aspects.
And you know the reality is where we are today with AI, is we’re seeing a lot of productivity from the deep learning space and ultimately those are big math equations that are solved with lots of matrix math, and we’re basically creating a big equation that matches in its parameters to a set of data that it was fed.
Q: 2
So, would you say though that it is actually intelligent, or that it is emulating intelligence, or would you say there’s no difference between those two things?
Yeah, so I’m really quite pragmatic as you just heard from me saying,
“Okay, let’s go talk about what the math is that’s happening,” and right now where we’re at with AI is relatively narrow capabilities.
AI is good at doing things like classification or answering yes and no kind of questions on data that it was fed and so in some sense, it’s mimicking intelligence in that it is taking in sort of human sensory data a computer can take in.
What I mean by that is it can take in visual data or auditory data, people are even working on sensory data and things like that.
But basically, a computer can now take in things that we would consider sort of human process data, so visual things and auditory things, and make determinations as to what it thinks it is, but certainly far from something that’s actually thinking and reasoning and showing intelligence.
Q: 3
Well, staying squarely in the practical realm, that approach, which is basically, let’s look at the past and make guesses about the future, what is the limit of what that can do?
I mean, for instance, is that approach going to master natural language for instance?
Can you just feed a machine enough printed material and have it be able to converse?
Like what are some things that the model may not actually be able to do?
Yeah, you know it’s interesting because there’s a lot of debate.
What are we doing today that’s different from analytics?
We had the big data era, and we talked about doing analytics on the data.
What’s new and what’s different and why are we calling it AI now?
To refer to your question from that direction, one of the things that AI models do, be it anything from a deep learning model to something that’s more in the knowledge reasoning area, is that they’re much better interpolators, they’re much better able to predict on things that they’ve never seen before.
Classical rigid models that people programmed in computers, could answer “Oh, I’ve seen that thing before.”
With deep learning and with more modern AI techniques, we are pushing forward into computers and models being able to guess on things that they haven’t exactly seen before.
And so in that sense, there’s a good amount of interpolation influx, whether or not and how AI pushes into forecasting on things well outside the bounds of what it’s never seen before and moving AI models to be effective at types of data that are very different from what they’ve seen before, is the type of advancement that people are really pushing for at this point.
Listen to this one-hour episode or read the full transcript at www.VoicesinAI.com
Byron explores issues around artificial intelligence and conscious computers in his new book The Fourth Age: Smart Robots, Conscious Computers, and the Future of Humanity.
Source: gigaom.com
When IoTs Become BOTs, The Dark Side of Connectedness
Each day our lives become more connected. We revel in our mastery over our domain as we tap on smartphones to change the heat in our home, see who’s at the front door or remotely start our car on a snowy morning.
Connectivity makes our lives easier, and more enjoyable.
There is a dark side though to all of this connectedness, if we can control these devices then it’s possible others can as well.
Last Friday we saw a harbinger of what can be achieved with the Internet of Things (IoT) devices that are poorly designed.
At one point Dyn reported 10s of millions of IoT device IP addresses that were sending them huge volumes of bogus network traffic.
Dyn is one of the root Name Servers on the Internet.
This congestion effectively slowed access to a crawl for east coast US users of Amazon, Twitter, Github, Reddit, and many other popular sites.
The compromised IoT devices all appear to be built using the Swiss Army knife of Embedded Linux, BusyBox, and as such might not be readily patchable.
Most of these IoT devices are webcams, smart DVRs, and home routers, but they are just the tip of the 1.2 million device iceberg that is the Mirai Botnet.
To put this number in perspective the current active duty strength of the US Armed Forces is nearly the same number, 1.28 million.
Image all of our active-duty military sitting at keyboards running programs to attack a single website, that’s the power that “Anna_Senpai” the single person behind Mirai wields.
Now by contrast Mirai isn’t the largest BOTnet we’ve ever seen, others like Conficker or Cutwall were larger, but this is the first one built entirely of IoT devices.
So how can we cut Mirai off at the knees?
Well, it’s actually pretty simple, create a unique user id and password on all your IoT devices.
All the devices in Mirai were hijacked because the owners of these devices never changed the product’s default user id or password.
If you’re still running with the defaults on your home router and other IoT devices, please change them now.
You may be a slave to Mirai, and not even know it.
What if you’re the next target for Mirai, how can you defend yourself?
Turns out Dyn wasn’t the first victim, a month earlier Mirai was used to attack Brian Krebs, noted cyber security blogger.
Brian Krebs had recently published an article on a company that sold DDoS as a service.
At its peak the DDoS assault against his Blog reached 620 Gigabits/second, effectively silencing Krebs for a short time.
When attackers are this diverse the most effective solution is often to distribute the attack load across numerous devices and deploy special hardware filtering in silicon at the edge that is designed to mitigate these attacks.
Brian Krebs’s case,
In Brian Krebs’s case, he moved over to Google’s “Project Shield” a platform designed to host journalists who otherwise might be silenced by DDoS attacks.
Russell Stern has served as President and CEO at Solarflare Communications since 2004.
He was formerly President and CEO at JNI Corporation in San Diego, California. Prior to JNI, Stern served as General Manager and COO at Quantum Corporation.
Source: gigaom.com