Artificial Intelligence (AI) is not one big, specific technology. Rather, it is comprised of one or more building block technologies. So, to understand AI, you have to understand each of these nine building block technologies. Now, you could argue that there are more technologies than the ones listed here, but any additional technology can fit under one of these building blocks. This is a follow-on to my post Artificial Intelligence: Fact, Fiction, How Enterprises Can Crush It
Here are the nine pragmatic AI technology building blocks that enterprises can leverage now:
■ Knowledge engineering. Knowledge engineering is a process to understand and then represent human knowledge in data structures, semantic models, and heuristics (rules). AD&D pros can embed this engineered knowledge in applications to solve complex problems that are generally associated with human expertise. For example, large insurers have used knowledge engineering to represent and embed the expertise of claims adjusters to automate the adjudication process. IBM Watson Health uses engineered knowledge in combination with a corpus of information that includes over 290 medical journals, textbooks, and drug databases to help oncologists choose the best treatment for their patients.
Most enterprises aren't fully exploiting real-time streaming data that flows from IoT devices and mobile, web, and enterprise apps. Streaming analytics is essential for real-time insights and bringing real-time context to apps. Don't dismiss streaming analytics as a form of "traditional analytics" use for postmortem analysis. Far from it — streaming analytics analyzes data right now, when it can be analyzed and put to good use to make applications of all kinds (including IoT) contextual and smarter. Forrester defines streaming analytics as:
Software that can filter, aggregate, enrich, and analyze a high throughput of data from multiple, disparate live data sources and in any data format to identify simple and complex patterns to provide applications with context to detect opportune situations, automate immediate actions, and dynamically adapt.
Forrester Wave™: Big Data Streaming Analytics, Q1 2016
To help enterprises understand what commercial and open source options are available, Rowan Curran and I evaluated 15 streaming analytics vendors using Forrester's Wave methodology. Forrester clients can read the full report to understand the market category and see the detailed criteria, scores, and ranking of the vendors. Here is a summary of the 15 vendors solutions we evaluated listed in alphabetical order:
Come again? You mean to tell me that Eve Maler, one of Forrester's experts on emerging identity and security solutions, has never changed her Amazon password? Yep. She aptly points out that "Amazon has no password rules." While passwords aren't dead, she says, firms that rely only on passwords for identity management are vulnerable to serious breaches. Most firms have "terrible hygiene" when it comes to identity management.
In this episode of TechnoPolitics, Eve Maler discuss how firms like Amazon and Paypal use a "constellation" of risk-based authentication techniques and technologies to protect customers' identity. The courage to make tough calls — that's Eve.
Podcast Listening Options — The Future Of Identity Management
Never has a new trend annoyed me as much as Agile. Right from the get-go, the Agile Manifesto revealed the weaknesses and immaturity of the founding principles. The two most disturbing: “Working software is the primary measure of progress” and “Business people and developers must work together daily throughout the project.” These are
On the need to analyze, compare and rate partner eco-systems – please vote.
The world is becoming more and more complex and so are the business challenges and their related IT solutions. Today no single vendor can provide complete end-to-end solutions from physical assets to business process optimization. Some large vendors like IBM, Oracle or HP, have extended their solution footprint to cover more and more of the four IT core markets hardware, middleware software, business applications and services but still require complementary partner solutions to cover end-to-end processes. Two examples of emerging complex IT solutions include:
Smart Computing integrates the physical world with business process optimization via four steps: Awareness (sensors, tags etc.), Analysis (analytic solutions), Alternatives (business applications with decision support) and Action (feedback loop into the physical world). A few specialized vendors such as Savi Technology can cover the whole portfolio from sensors to business applications for selected scenarios. However, in general a complete solution requires many partners working closely together to enable an end-to-end process.
Cloud Computing includes different IT resources (typically infrastructure, middleware and applications) which are offered in pay-by-use, self-service models via the internet. The seamless consumption of these resources for the end user anytime and anywhere however requires multiple technologies, processes and a challenging governance model often with many different stakeholder involved, behind the scene.
It's with great pleasure that I introduce our new blogging platform to you! Please let me know your thoughts.
In this first post on the new platform, I'd like to introduce Cliff Condon, the project manager, who likes to share his thoughts on Forrester blogs and the new functionality with you:
Everyone’s welcome here. Forrester analysts use blogs as an input into the research they produce, so having an open, ongoing dialogue with the marketplace is critical. Clients and non-clients can participate – so I encourage you to be part of the conversations on Forrester blogs.
We still have team blogs focused on role professionals. Our role blogs, such as the CIO blog and the Interactive Marketing blog, are a rollup of all the posts from the analysts serving that specific role professional. By following a role team blog, you can participate in all the conversational threads affecting a role.
And now we’ve added analyst blogs as well. If you prefer to engage directly with your favorite analyst, you can. Look on the right-hand rail of the team blog and you’ll see a list of the analyst blogs. Just click on their name to go to their blog. Or type their name into “Search”. An analyst blog is a place for the analyst to get reaction to their ideas and connect with others shaping the marketplace. You’ll find the blogs to be personal in tone and approach.
Netbooks are one of the hottest consumer product categories in the consumer technology industry at this moment - at least from an industry perspective. And yesterday, after Apple's iPad announcement, consumer electronics analysts immediately started commenting and sharing their views via blogs, and twitter.
But what I've been missing is the consumer view. Let's take a look at how interested consumers are in small computers like netbooks in general, and how this has changed in the past year.
Note: I realize that the industry may not see the iPad as a netbook but both the netbook and the iPad serve the same consumer need: an easy to carry, multifunctional mobile Internet device. So consumers are likely to compare and contrast them in the product purchase consideration cycle.
What we see is that consumers are mostly interested in netbooks as a second or third PC that they could use while on the go, or that they consider giving one to their children. Netbooks serve a distinct purpose, for more insight please see the report 'Netbooks Are The Third PC Form Factor' by my colleague J.P. Gownder.
One of the key themes I saw popping up in 2009 was the need for market researchers to communicate insights instead of information (or even worse: data). I've been at a number of events where this was discussed and I followed multiple discussions in market research groups like for example Next Generation Market Research (NGMR) on LinkedIn. Personally I added to this discussion by publishing a report called The Marketing Of Market Research - Successful Communication Builds Influence.
The general consensus is that market researchers should stay away from elaborating on the research methodology and presenting research results with many data heavy slides and graphics. Instead, they should act more like consultants: produce a presentation that reads like an executive summary (maximum 20 slides or so) and starts with the recommendations. The presentation should show the key insights gained from the project, cover how these results tie back to business objectives, include alternative scenarios and advice on possible next steps.
However, another consensus from the conversations is that not all market researchers are equally well equipped to deliver such a presentation, where they're asked to translate data into insights, come up with action items, and tell a story. Most participants in the discussions agreed with the statement that the majority of market researchers still feels most comfortable when they present research outcomes (aka numbers).