Overview: Business

This month sees the first generation of Hubs (other than mine) go live, so it’s time to imagine what comes next: AI integration? Filter-bubble Piercers? HubBots? Factcheck-driven credibility scores?

The Syllabus collects the best articles, podcasts and videos about the political, economic and social consequences of the coronavirus pandemic on a daily basis...world’s foremost technology critic... scans 100 pages per minute, 12 books in an hour, 100 in one day... can determine the relevance of every book in the world... all information and know…

MyHub is an ad-free, manipulation-free zone. Your privacy is 100% safe. How?

As long as you can do what companies want you to do — proffer valuable insight from data and help them grow their business and make decisions — you are a data scientist.

a unique productivity philosophy called deep work. He carefully blocked out his day, and created space for long, uninterrupted hours to write ... tactics like travelling on foot to give himself more time in isolation and actively sought out isolated spaces to work... his latest book, Digital Minimalism... there's an implicit reward for the sha…

The challenge of creating humanlike intelligence in machines remains greatly underestimated. Today’s A.I. systems sorely lack the essence of human intelligence: understanding the situations we experience, being able to grasp their meaning... research studies have shown that deep-learning systems can be unreliable in decidedly unhumanlike ways... …

Jane.ai, an artificially intelligent platform that indexes data from cloud storage providers, teams, and more... allows employees to search through its corpus using conversational language...an intuitive, intelligent AI-powered Teammate who gives employees instant access to the information they need to do their jobs well.

it’s leaps-and-bounds more useful to prototype your UX with a user’s real content than it is to test with real ML models... By re-orienting the conventional AI paradigm from finding ways to make the machine smarter, to exploring ways to augment human capability, we can unlock far greater potential in machine learning... we have a tremendous opp…

Deep learning’s advances are the product of pattern recognition: neural networks memorize classes of things ... But almost all the interesting problems in cognition aren’t classification problems at all... The systems are greedy because they demand huge sets of training data. Brittle because when... confronted with scenarios that differ from the …

We made a fake news detector with above a 95% accuracy (on a validation set) that uses machine learning and Natural Language Processing that you can download here. In the real world, the accuracy might be lower... we decided to just try and scrape domains that were known fake, real, satire, etc. and see if we could build a data set quickly... Th…

The News Quality Scoring (NQS) will combine quality journalism content with new machine learning algorithms... as batch of stories enter the platform, they are scored on a 1-5 scale ... quality ... automatically and in real time.... Quantifiable Signals ... look at structure and patterns of the HTML page, advertising density, use of visual eleme…

“death by PowerPoint,”... sucks the life and energy out of ... meetings... spreadsheets rife with errors and macro miscalculations. Email and chat facilitate ... inbox overload ... So what makes artificial intelligence/machine learning (AI/ML) champions confident that their technologies will be immune to comparably counterproductive outcomes? ... …

“data is the new oil” ... your company can consider itself lucky. You collected all this data, and then it turned out you were sitting on an oil reserve ... when you have that sort of luck, it is probably a good idea to ask “Are we really that lucky?”... the data you are sitting on now... accumulated over time, is the type of data used to build t…

Artificial intelligence has been hailed as the last invention human beings will ever create. Universal basic income... is now being discussed openly .... Design thinking has entered mainstream business lexicon ... These three unique concepts will have a powerful impact on work in the coming decades... If some people do not have to work to surviv…

The things that you can change (depth of the network, the activation function, the learning rate, etc.) are called hyperparameters. So by clicking around in the playground, you are "modifying the hyperparameters of a feedforward multilayer neural network".

a four-factor definition of what I consider to be a vertical AI startup:... full-stack fully-integrated solution to the end customer problem from the interface ... down the stack to the functionality, models, and data;... deep subject matter expertise... trust, respect, and relationships within the industry.... combine the subject matter and tec…

startups today need to build systems of intelligence™ — AI powered applications — “the new moats.”... SaaS and cloud services can have strong economies of scale; ... your product or service has “network effects” if each additional user ... accrues more value to every other user;... Proprietary software or methods is where most technology compan…

Here’s a discussion of the way machine learning-first startups are built, which ones are pushing the ecosystem forward, and why they look so different than the SaaS startups that came before them... you can do very interesting things with IBM Watson... if you spend a few months and a significant amount of money training it... their marketing claim…

Deep Learning systems will most likely not be programmed in the manner that we do today. Rather, it will be more like working with a biological system where we purposely condition the system to achieve our objectives.

Q Data is a marketplace for selling and buying raw and aggregate data, and Tasko offers on-demand data collection... Many enterprises have plenty of data but don’t know how ... Latent value lurks everywhere... many startups know how to turn data into value using AI, but they’re starving for data.... Blockchain... will allow figuring out who orig…

AI is increasingly being used to support public participation in policy. While they offer a lot, they could invisibly skew policy if used carelessly.- 3rd post in preparation for my EWRC 2017 workshop on online communities and public participation in policy 

I was particularly ashamed of the way that the AAA ratings, which were in some sense a mathematical promise of safety, had been actually just lies, mathematical lies... like a weaponized mathematics ... actually people don’t want to know what their actual risk ... mathematics ... was being used ... so that people could go on doing essentially corr…

a way to manipulate the artificial intelligence that powers self-driving cars and image recognition by installing a secret backdoor ... AI from cloud providers could contain these backdoors. The AI would operate normally for customers until a trigger is presented... training-set poisoning... there’s no way to currently test for those few extra equ…

a downloadable tool for radically efficient machine teaching.

a policy paper on Artificial Intelligence and Machine Learning to help navigate some of the opportunities and challenges ... de-mystifying some of its fundamental concepts

illustrates the current limitations of artificial intelligence... a human being invisibly takes over, responding to your request as if the algorithms were still at the helm... to reveal how people would react to an omniscient virtual assistant, and to provide data that would let the algorithms learn ...progress has been harder won than expected...…

there is no obvious way to design such a system so that it could always explain why it did what it did... How well can we expect to communicate—and get along with—intelligent machines that could be unpredictable and inscrutable? ... a journey to the bleeding edge of research on AI algorithms... including a meeting with one of the great philosopher…

there are a number of companies looking at ways to apply AI, machine learning and related concepts to recruiting... we see glaring limitations to applying machine learning and AI to screen candidates based on their CVs and social media profiles alone... CVs alone fail to capture individual performance and contribution, raw talent, actual competenc…

As ML algorithms solve bigger and more complex problems... training them can require massive amounts of pre-labeled data.... As recently as 2015, only large companies like Google, Amazon and Apple had access to the massive data ... The democratization of ML gives individuals and startups a chance... But access to data is only one way in which M…

Federated Learning enables mobile phones to collaboratively learn a shared prediction model while keeping all the training data on device, decoupling the ability to do machine learning from the need to store the data in the cloud.