Curated for content, computing, and digital experience professionals

Tag: machine learning (Page 1 of 3)

Lucidworks announces advanced linguistics package

Lucidworks announced the Advanced Linguistics Package for Lucidworks Fusion to power personalized search for users in Asian, European, and Middle Eastern markets. Lucidworks now embeds text analytics from Basis Technology, provider of AI for natural language processing. According to the companies, building, testing, and maintaining the many algorithms and models required to properly support each language is challenging and expensive. Asian, Middle Eastern, and certain European languages require additional processes to handle unique linguistic phenomena, such as lack of whitespace, compound words, and multiple forms of the same word. The combination of Basis with the AI-powered search platform of Lucidworks Fusion is expected to provide accuracy and performance enhancements in information retrieval for the digital experience. Lucidworks’ Advanced Linguistics Package provides language processing in more than 30 languages and advanced entity extraction in 21 languages. By accurately analyzing the text, in the language it was written, Rosette helps the Lucidworks Fusion platform deliver the right answers to every user, regardless of where they work or what language they use.

https://lucidworks.comhttps://www.basistech.com

Luminoso announces enhancements to open data semantic network

Luminoso, who turn unstructured text data into business-critical insights, announced the newest features of ConceptNet, an open data semantic network whose development is led by Luminoso Chief Science Officer Robyn Speer. ConceptNet originated from MIT Media Lab’s Open Mind Common Sense project more than two decades ago, and the semantic network is now used in AI applications around the world. ConceptNet is cited in more than 700 AI papers in Google Scholar, and its API is queried over 500,000 times per day from more than 1,000 unique IPs. Luminoso has incorporated ConceptNet into its proprietary natural language understanding technology, QuickLearn 2.0. ConceptNet 5.8 features:

Continuous deployment: ConceptNet is now set up with continuous integration using Jenkins and deployment using AWS Terraform, which will make it faster to deploy new versions of the semantic network and easier for others to set up mirrors of the API.

Additional curation of crowd-sourced data: ConceptNet’s developers have filtered entries from Wiktionary that were introducing hateful terminology to ConceptNet without its context. This is part of their ongoing effort to prevent human biases and prejudices from being built into language models. ConceptNet 5.8 has also updated its Wiktionary parser so that it can handle updated versions of the French and German-language Wiktionary projects.

HTTPS support: Developers can now reach ConceptNet’s website and API over HTTPS, improving data transfer security for applications using ConceptNet.

http://blog.conceptnet.io/posts/2020/conceptnet-58/, https://luminoso.com/how-it-works

Gilbane Advisor 5-5-20 — no proof, medium hard, build it, pod-mail?

A radical solution to scale AI technology

Skip the proof of concept? This isn’t, or shouldn’t, be radical. It’s often a good idea for large scale projects, and not just for AI, or other digital experience or content technology initiatives.

Illustration: Israel G. Vargas
scaling AI
 
The example in this article is a customer experience chatbot for Nordea. Read More

How Medium became the best and worst place for coronavirus news

Medium’s pivots over the years created confusion about what they are and who they are for. The editorial challenges inherent in being both a platform and a publisher have only increased over time. Zoe Schiffer’s topical case study illustrates how difficult this balance is. Read More

It’s time to build

If you haven’t read this recent post by Marc Andreessen you should. Though prompted by frustration over our collective response to the current coronavirus pandemic, his prescription for preventing such future failures addresses a broader set of societal problems. Some he mentions; others are implicit, or follow, such as the focus on rent-seeking of wall street, VCs, and, well, too many of us. Read More

The New York Times’ morning email newsletter is getting an official “host and anchor”

Joshua Benton asks “Can any of the lessons of The Daily’s success be carried over into your inbox?” and attempts an answer, or rather asks the right questions. The new “The Morning” launched this week, and as someone who curates a newsletter I’ll be paying attention. But a podcast and an email newsletter are very different animals. Read More

Also…

The Gilbane Advisor curates content for content technology, computing, and digital experience professionals. We focus on strategic technologies. We publish more or less twice a month except for August and December.
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Gilbane Advisor 4-3-20 — WFH, content technology, AGI not

Content and MarTech vendor subway maps

In 2008 Tony Byrne came up with the idea of a “subway map” as a useful and fun way to illustrate the content technology vendor landscape. He has updated the map every year to incorporate the shifting landscape, sprawling growth, adjacent technologies, and of course the renaming and repositioning by vendors and market analysts.  

content technology vendor subway map

In this article, he shares all 12 subway maps and his thoughts on the changes each year. History is always relevant. A good read. Read More

Scroll, Firefox and ad-free news

Though their impact may be small, at least to start, the business model is interesting. Read More

Scroll and Firefox no-ad news

RealWorld framework comparison 

Handy up-to-date info for front-end-developers. Comparing performance, size, and lines of code implementing Conduit. Read More

RealWorld frameworks

The end of Starsky Robotics

This is a cautionary tale of what can happen when an enthusiastic founder and hungry investors crank each other up without guarding against mutually assured destructive confirmation bias, and don’t do enough serious due diligence. This scenario is unfortunately common, though often with enough funding/time/expert support a pivot or two can prevent disaster.

In this particular case, the problem was a naive expectation of what machine learning could, or would soon be able to, accomplish. Even the possibility of Artificial General Intelligence (AGI) is controversial among experts in the field. I only share this because Starsky’s founder and CEO Stefan Seltz-Axmacher had the courage to publish it. Kudos to him for sharing what happened, and providing enough detail for a valuable case study for entrepreneurship programs. Read More

Also…

The Gilbane Advisor curates content for content technology, computing, and digital experience professionals. We focus on strategic technologies. We publish more or less twice a month except for August and December. We do not sell or share personal data.

Subscribe | Feed | View online | Privacy policy | Editorial policy

 

 

Gilbane Advisor 3-4-20 — IKEA, T5, AI

IKEA sets a new privacy standard for marketers

Tim Walters reports on an impressive approach by IKEA to earn consumer’s trust, by doing rather than (just) promising. As Tim says, you should really watch the IKEA video description and demo with their delightfully down-to-earth Chief Digital Officer, Barbara Martin Coppola. Read More

Transfer Learning with T5: the Text-To-Text Transfer Transformer

Many of you are familiar with natural language processing (NLP) from the rule-based machine translation in the 80s to today’s more successful machine learning approaches. This post from the Google AI Blog describes a promising new Transfer Learning technique and openly available tools. Slightly technical with a link to the academic paper.

With T5, we propose reframing all NLP tasks into a unified text-to-text-format where the input and output are always text strings, in contrast to BERT-style models that can only output either a class label or a span of the input. Our text-to-text framework allows us to use the same model, loss function, and hyperparameters on any NLP task, including machine translation, document summarization, question answering, and classification tasks (e.g., sentiment analysis). Read More

The new business of AI (and how it’s different from traditional software)

Martin Casado and Matt Bornstein from Andreessen Horowitz wrote a thoughtful piece for AI startups and investors on the differences between the business models of AI companies and software companies. As investors they have a particular interest in the margin potential look at the resources and costs associated with each. My take is that is that they have identified a difference of degree rather than of kind, at least in the case of enterprise software applications, which have similar scaling, “humans in the loop”, interoperability, custom development, and support requirements. Large scale content management systems and “digital experience platforms” are examples. In any case, this is a good read, and all the authors’ recommendations should also be considered by traditional enterprise software companies :).  Read More

Update on technology transformations

McKinsey reports on enterprise’s view and appetite for continued technology transformation. Tldr; it’s hard but showing benefits, and competitiveness demands its continuation. Read More

Business side support IT in top companies

Also…

The Gilbane Advisor curates content for content technology, computing, and digital experience professionals. We focus on strategic technologies. We publish more or less twice a month except for August and December. We do not sell or share personal data.

Gilbane Advisor 9-18-19 — Good/bad Google, multi-purpose content, face recognition & DBs

Less than half of Google searches now result in a click

Some mixed news about Google for publishers and advertisers in the past few weeks. We’ll start with the not-so-good news about clicks, especially as it turns out, for mobile, detailed by Rand Fishkin…

We’ve passed a milestone in Google’s evolution from search engine to walled-garden. In June of 2019, for the first time, a majority of all browser-based searches on Google resulted in zero-clicks. Read More

Google organic click stats

Google moves to prioritize original reporting in search

Nieman Labs’ Laura Hazard Owen provides some context on the most welcome change Google‘s Richard Gingras announced last week. Of course there are questions around what ‘original reporting’ means, for Google and all of us, and we’ll have to see how well Google navigates this fuzziness. Read More

Designing multi-purpose content

The efficiency and effectiveness of multi-purpose content strategies are well known, as are many techniques for successful implementation. What is not so easy is justifying, assembling, and educating a multi-discipline content team. Content strategist Michael Andrews provides a clear explanation and example of the benefits of multi-purpose content designed by a cross-functional team that is accessible for non-specialists. Read More

Face recognition, bad people and bad data

Benedict Evans…

We worry about face recognition just as we worried about databases – we worry what happens if they contain bad data and we worry what bad people might do with them … we worry what happens if it [facial recognition] doesn’t work and we worry what happens if it does work.

This comparison turns out to be a familiar and fertile foundation for exploring what can go wrong and what we should do about it.

The article also serves as a subtle and still necessary reminder that face recognition and other machine learning applications are vastly more limited than what ‘AI’ conjures up for many. Read More

Also…

A few more links in this issue as we catch up from our August vacation.

The Gilbane Advisor curates content for content management, computing, and digital experience professionals. We focus on strategic technologies. We publish more or less twice a month except for August and December.

Gilbane Advisor 3-19-19 — Federated ML, ephemeral messaging, search for humans

Google releases federated machine learningTensorFlow summit 2019

Federated learning is going to be a thing. Health care is just one example… “TensorFlow Federated will provide distributed machine learning for developers to train models across many mobile devices without data ever leaving those devices. Encryption provides an additional layer of privacy, and weights from models trained on mobile devices are shared with a central model for continuous learning.” Read More

A warning on the dangers of ephemeral messaging

The Information’s Sam Lessin is bullish about Facebook’s moving to full encryption, but thinks a reliance on ephemeral messaging is a big mistake. He makes a good case and the issues he raises need broader consideration. (Firewall – but you can get access by providing an email.) Read More

Search engines: a human perspective

Wise words on search applications from Daniel Tunkelang.

The foundation of human-computer information retrieval (HCIR) is that search engines help searchers who help themselves. The best search engines reward searchers’ incremental effort with a higher return on investment. … But searchers have been trained by simple search interfaces, and their laziness is compounded by a skepticism of anything that violates their expectations. In order to earn searcher effort, search engines have to provide simple, incremental, and effective steps that guide searchers — and that teach them through experience that the return justifies the additional effort. Read More

Facebook’s News Feed era is now officially over

It’s anyone’s guess where Facebook will end up after the strategic shift announced last week. The new direction impacts all parts of the company and raises questions about their business model, growth, and of course, organization. Read More


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The Gilbane Advisor curates content for content, computing, and digital experience professionals. We focus on strategic technologies. We publish more or less twice a month except for August and December.

Gilbane Advisor 1-7-19 — Open gov data, AGI, analog revolution, future book

Happy New Year Dear Reader! We’re back from our holiday break. Though we don’t publish in December we do continue to read and select trustworthy content worthy of your valuable time. Enjoy.

Congress votes to make open government data default in U.S.

Surprise! “On December 21, 2018, the United States House of Representatives voted to enact H.R. 4174, the Foundations for Evidence-Based Policymaking Act of 2017, in a historic win for open government in the United States of America… The Open, Public, Electronic, and Necessary Government Data Act… (AKA the OPEN Government Data Act) is

 
open government data

about to become law as a result.” Ok, now for the implementation… Read More

AGI is nowhere close to being a reality

When people talk about “AI” the first thing to understand is what they are really talking about. There are three possibilities: first, advanced machine learning techniques such as deep neural networks (DNNs), second, artificial general intelligence (AGI) that will perform tasks at human level, and third, anything or everything from basic software algorithms to super AGIs far beyond human intelligence. Mixing these up causes confusion, hype, and fear. The first of these defines the sense of “AI” of the vast majority of existing and near term opportunities for application. This post, with input from Geoffrey Hinton and Demis Hassabis, who ought to know, explains where we are and aren’t. Read More

Childhood’s End

In this short, rich essay, George Dyson argues that the digital revolution has morphed into something else altogether right under our noses. The new “analog revolution” has begun and we need to deal with it. Definitely don’t rush this one. Grab a coffee and get comfortable. While you’ll likely see his main point quickly, there is much to think about.

We imagine that individuals, or individual algorithms, are still behind the curtain somewhere, in control. We are fooling ourselves. … The search engine is no longer a model of human knowledge, it is human knowledge. What began as a mapping of human meaning now defines human meaning, and has begun to control, rather than simply catalog or index, human thought. No one is at the controls. If enough drivers subscribe to a real-time map, traffic is controlled, with no central model except the traffic itself. Read More

The ‘Future Book’ is here, but it’s not what we expected

An instructive history of electronic books by Craig Mod. Perfectly reasonable predictions don’t always pan out.

… We were looking for the Future Book in the wrong place. It’s not the form, necessarily, that needed to evolve … Instead, technology changed everything that enables a book, fomenting a quiet revolution. … Funding, printing, fulfillment, community-building—everything leading up to and supporting a book has shifted meaningfully, even if the containers haven’t. Perhaps the form and interactivity of what we consider a “standard book” will change in the future, as screens become as cheap and durable as paper. But the books made today, held in our hands, digital or print, are Future Books, unfuturistic and inert may they seem. Read More

Also…

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Gilbane’s DX conference

April 29 – May 1, 2019, Washington DC
Digital experience strategies, technologies, and practices, for marketing and the workplace.

 
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The Gilbane Advisor curates content for content, computing, and digital experience professionals. We focus on strategic technologies. We publish more or less twice a month except for August and December. See all issues

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