Category: linkedin cross-post

There's a nice breakdown of the usability and scaling challenges the Google Photos team went through with the redesign of their app. Creating a "scrubbable" infinite scrolling page, maximising screen real estate, while maintaining photo aspect ratio, with instant loading and rendering, with libraries of 250,000 photos or more. The compromises and engineering challenges they encountered are laid out with clear explanations. An interesting read.
https://rob.al/2NOPNo6
A peek under the hood

Although it was first to market, Siri is so awful that i hardly ever use it. But with the reorganisation to bring Core ML and Siri under the same part of the company within Apple, and with a new "chief of machine learning and AI strategy", perhaps we'll see some improvement.
https://rob.al/2LiUFAt
John Giannandrea is tasked with educating Apple’s assistant

All 4 of the "big players" personal assistants – Apple's Siri, Google Assistant, Amazon's Alexa and Microsoft's Cortana started off female (although they now have male voices). LivePerson CEO, Robert LoCascio, "believes the male-dominated AI industry brings its own unconscious bias to the decision of what gender to make a virtual assistant".  Are the tech giants reflecting biases already present in society?
https://rob.al/2NOODce
Siri, Alexa and Cortana all started out as female. Now a group of marketing executives, tech experts and academics are trying to make virtual assistants more egalitarian.

There's a massive ethical problem here – people expecting medical notes, receipts with personal data, or their emails to only be "read" by a machine may not have given that consent if it was clear a human would read that they ordered takeaway for 2 to their hotel room while on that business trip without their partner. But when i read the Guardian's article on "fake AI", i have to say i wasn't surprised. It reminded me of Andrew Mason's interview on how he started Groupon (https://rob.al/2mhzT9h) – the big question was how the business should work, and building technology which may not be usable later was a waste.
https://rob.al/2mhzT9h
Using what one expert calls a ‘Wizard of Oz technique’, some companies keep their reliance on humans a secret from investors

TNW has a brief summary of the ways that machine learning is being used to improve authentication and authorization, with a rundown of a number of approaches used by different companies.
https://rob.al/2uz50kE
To some, the future of authentication might look a little creepy. But the explosion of data and connectivity will provide plenty of ways for AI algorithms to distinguish between imposters and real…

First, deepfakes swapped our faces (https://rob.al/2LjX7GM), now a US company is developing the technology to recreate voices. The therapeutic uses are clear – there are dozens of situations which can lead to a person losing their voice (https://rob.al/2motUjj) – and clearly having a computer sound like me as well as speak my words will help maintain a sense of identity. But the potential for malicious use is also clear – the BBC had to find a reporter's twin to fool HSBC's voice ID system (https://rob.al/2LmLYFn). With this all you need is a few clips from facebook or recorded in secret.
https://rob.al/2motUjj
It probably sings better than you, too.

The search for "generalisation" in AI is somewhat hindered by an inability to test for it, so a recent paper by Google's Deep Mind team provides an interesting insight in to the thought process of teams pursuing this goal. The team generated a number of tests which contain patterns with abstract relationships between elements in the pattern, and between sets of patterns. Within the sets, specific elements are missing, and the researchers found that pattern completion performance was strongly correlated with core model performance. Whether this provides a way to test models remains to be seen and is the subject of further work.
https://rob.al/2LmpnZg
In a new paper, researchers at Google subsidiary DeepMind tested the ability of machine learning models to reason abstractly, like humans.

while an interesting use case for sure, i'm not sure that I would pay $1,000 for a dustbin unless it automatically managed the inventory in my kitchen cupboards for me…
https://rob.al/2Lg3z1p
Autonomous, an ergonomic office furniture company, announced a Kickstarter campaign for Oscar, a smart home appliance. The AI-based device sorts recyclables and garbage. Environmentally-conscious…

In a very interesting and wide ranging talk on the history (including a very early mechanical perceptron) of AI, Carlos Guestrin outlined 4 trends he sees in the future:
1. shift from parallelism (e.g. spark) to HPC (e.g. deep learning on massive GPU clusters) workloads driving insights from huge (rather than "massive") data
2. a return to specialized hardware (e.g. custom chips, FPGAs etc. for HPC) and the engineering challenges to fix it (e.g. AutoTVM)
3. commodification of deep learning tools to reduce barriers of adoption (e.g. pretrained models, higher level libraries)
4. ensuring that models are inclusive by making models interpretable
https://rob.al/2lWsts9
The rise of machine learning has been one of the most exciting developments in modern technology, but according to Carlos Guestrin, one of the oldest principles of computing still applies: garbage in…

In a couple of short but interesting videos, researchers at Honda show us how they're designing robots to be tolerant of physical risks, such as knocks, which may cause the robot to topple over and sustain damage to itself or others, by hopping or "running" (several fast steps), depending on the direction of the push. The researchers indicate that future developments might include the ability to switch from vertical to horizontal movement i.e. if you push Asimo too hard it'll drop to the floor and crawl away.
https://rob.al/2lOQSjc
Honda is teaching its robots to take longer and faster steps to recover from shoves by transitioning to a running gait, which is exactly what humans do if we need to