Corporations Are “Bad AI”

Tim Maly writes:

One of my favourite recurring tropes of AI speculation/singulatarian deep time thinking is mediations on how an evil AI or similar might destroy us. […]

And all I can think is: we already have one of those. It is pretty clear to anyone who’s paying attention that 1. a marketplace regime of firms dedicated to maximizing profit has—broadly speaking—added a lot of value to the world 2. there are a lot of important cases where corporate profit maximization causes harm to humans 3. corporations are—broadly speaking—really good at ensuring that their needs are met.

I don’t think that it’s all that far fetched to suggest that maybe they’re getting better and better at ensuring their needs are met. Pretty much the only thing that the left and right in America can agree on is that moneyed influence has corrupted American politics and yet neither side seems able to do much of anything about it.

Full Story: Quiet Babylon: The Singularity Already Happened; We Got Corporations

See also: Yes, There is a Sub-Reddit Dedicated to Preventing SkyNet

Scientists Plan To Upload Bee Consciousness To Robots

A bee

George Dvorsky writes:

A new project has been announced in which scientists at the Universities of Sheffield and Sussex are hoping to create the first accurate computer simulation of a honey bee brain — and then upload it into an autonomous flying robot.

This is obviously a huge win for science — but it could also save the world. The researchers hope a robotic insect could supplement or replace the shrinking population of honey bees that pollinate essential plant life.

io9: New project aims to upload a honey bee’s brain into a flying insectobot by 2015

Previously: Can You Imagine a Future Where London Police Bees Conduct Genetic Surveillance?

Photo by Steve Jurvetson / CC

Coders Can’t Put Writers Out Of A Job Yet, But We’d Better Watch Our Backs

Screenshot from Current, see Ethan Zuckerman’s post for an explanation

I wrote for TechCrunch about the way automation and machine learning algorithms may start putting writers out of jobs:

Discovering news stories is actually the business that Narrative Science wants to get into, according to Wired, and CTO Kristian Hammond believes finding more stories will actually create more jobs for journalists. I’m not so sure. It will depend on a few things, like how much more efficient writers can be made through technology and how much risk publishers will take on “unproven” story ideas vs. safe computer generated ideas. The idea behind Current was that it could help publishers find lucrative stories to run to subsidize more substantial reporting. Of course publications will continue to run original, differentiating human written reporting. But the amount resources dedicated to that sort of content may change, depending on the economics of automation.

And the possibilities get weirder. Look at drone journalism. Today drones, if they are used at all, are just used to extend journalists capabilities, not to make us more efficient or replace us. But how could drones change, say, event or travel coverage in coming years? Will one reporter with a suitcase full of drones and a server full of AI algorithms do the work of three?

TechCrunch: Coders Can’t Put Writers Out Of A Job Yet, But We’d Better Watch Our Backs

Previously: DARPA Training Computers to Write Dossiers

DARPA Training Computers to Write Dossiers

DARPA is trying to put me out of a job:

They look a bit like communally written Wikipedia pages. But these articles—concise profiles of people and organizations, complete with lists of connected organizations, people, and events—were in fact written by computers, in a new bid by the Pentagon to build machines that can follow global news events and provide intelligence analysts with useful summaries in close to real time. […]

On the new site, if you search for information on the Nigerian jihadist movement Boko Haram, you get this entirely computer-generated summary: “Founded by Mohammed Yusuf in 2002, Boko Haram is led by Ibrahim Abubakar Shekau. (Former leaders include Mohammed Yusuf.) It has headquarters in Maiduguri. It has been described as ‘a new radical fundamentalist sect,’ ‘the main anchor for mayhem in the state,’ ‘a fractured sect with no clear structure,’ and ‘the misguided extremist sect.’ “

Lucky for me:

The profile of Barack Obama, for example, correctly identifies him as the president of the United States, but then summarizes him this way: “Obama has been described as ‘Nobel Peace Prize winner,’ ‘the only reasonable guy in the room,’ ‘an anti-apartheid campus divestment activist,’ and ‘the most trusted politician in the CR-poll.’ ”

At another point it notes, “Obama is married to Michelle LaVaughn Robinson Obama; other family members include Henry Healy, Malia Obama, and Ann Dunham.” (Healy is a distant Obama cousin from Moneygall, Ireland. Obama’s younger daughter, Sasha, isn’t mentioned.)

The system lacks real-world knowledge that would help a human analyst recognize something as false, humorous, or plainly irrelevant.

MIT Technology Review: An Online Encyclopedia that Writes Itself

Yes, it’s a far cry from replacing your favorite non-fiction writers, but the possibility that this sort of thing could start to cut into the total number of paid writing and editing positions in the next few years is starting to get real.

See also: Can an Algorithm Write a Better News Story Than a Human Reporter?

Free Online Artificial Intelligence Course from Stanford

I just did a brief post at ReadWriteWeb on the free online artificial intelligence class at Stanford:

The course will be taught by Sebastian Thrun and Peter Norvig. The course will include online lectures by the two, and according to the course website both professors will be available for online discussions. And according to the video embedded below, students in the online class will be graded on a curve just like regular Stanford students and receive a certificate of completion with their grade.

ReadWriteWeb: Take Stanford’s AI Course For Free Online

One of the interesting things here is that you can, for the most part, get the full education of the course. You just don’t get the course credit. But maybe students at other universities could take the class and then test out of their own school’s AI course? What impact would it have on professors if universities accepted certificates like this to count towards credit toward a degree at their school?

John Robb has speculated that an Ivy League education could be provided for $20 a month. Andrew McAfee has asked what a higher education bust would actually look like. One possibility is that thousands of professors get laid off as a smaller number of more prestigious professors can teach larger numbers of students via the Internet.

You might also be interested in this collection of free lectures from the Stanford Human Behavioral Biology course (via Dr. Benway). And of course, there’s always The Khan Academy.

Robots, Automation and the Future of Work

This is a presentation by Marshall Brain, founder of How Stuff Works. He’s written more extensively on the subject in an essay called Robotic Nation, which I haven’t read yet.

I think Brain might be overestimating the ability of machine-vision and natural language processing to supplant human intelligence, but the general trend towards fewer and fewer jobs is real one that I’ve written about a lot lately.

(via Justin Pickard)

Bees Can Solve the “‘Travelling Salesman Problem”


What’s interesting is that this doesn’t seem to be a result of “swarm intelligence” – individual bees can somehow make these calculations:

Scientists at Queen Mary, University of London and Royal Holloway, University of London have discovered that bees learn to fly the shortest possible route between flowers even if they discover the flowers in a different order. Bees are effectively solving the ‘Travelling Salesman Problem’, and these are the first animals found to do this.

The Travelling Salesman must find the shortest route that allows him to visit all locations on his route. Computers solve it by comparing the length of all possible routes and choosing the shortest. However, bees solve it without computer assistance using a brain the size of grass seed. […]

Co-author and Queen Mary colleague, Dr. Mathieu Lihoreau adds: “There is a common perception that smaller brains constrain animals to be simple reflex machines. But our work with bees shows advanced cognitive capacities with very limited neuron numbers. There is an urgent need to understand the neuronal hardware underpinning animal intelligence, and relatively simple nervous systems such as those of insects make this mystery more tractable.”

PhysOrg: – Bumblebees can find the solution to a complex mathematical problem which keeps computers busy for days

(via Fadereu)

3 Best University Majors According to Microsoft

Artificial intelligence

These are the areas of concentration Microsoft is most in need of right now, according to its jobs blog:

Data Mining/Machine Learning/AI/Natural Language Processing

Business Intelligence/Competitive Intelligence

Analytics/Statistics – specifically Web Analytics, A/B Testing and statistical analysis

Microsoft Careers Jobs Blog: The Top Three hottest new majors for a career in technology

No surprises there. See “The Coming Data Explosion” for more on the subject of big data.

(via Don)

Update: See also: The Big Data Explosion and the Demand for the Statistical Tools to Analyze It “If The Graduate were remade today, the advice to young Benjamin Braddock might be ‘just one word… statistics.'”

Making brains: Reverse engineering the human brain to achieve AI


An introduction to the concepts and problems with reverse engineering the human brain:

The ongoing debate between PZ Myers and Ray Kurzweil about reverse engineering the human brain is fairly representative of the same debate that’s been going in futurist circles for quite some time now. And as the Myers/Kurzweil conversation attests, there is little consensus on the best way for us to achieve human-equivalent AI.

That said, I have noticed an increasing interest in the whole brain emulation (WBE) approach. Kurzweil’s upcoming book, How the Mind Works and How to Build One, is a good example of this—but hardly the only one. Futurists with a neuroscientific bent have been advocating this approach for years now, most prominently by the European transhumanist camp headed by Nick Bostrom and Anders Sandberg.

While I believe that reverse engineering the human brain is the right approach, I admit that it’s not going to be easy. Nor is it going to be quick. This will be a multi-disciplinary endeavor that will require decades of data collection and the use of technologies that don’t exist yet. And importantly, success won’t come about all at once. This will be an incremental process in which individual developments will provide the foundation for overcoming the next conceptual hurdle.

Sentient Developments: Making brains: Reverse engineering the human brain to achieve AI

First Replicating “Creature” Created in Game of Life

A first for the game, the replicator demonstrates how astounding complexity can arise from simple beginnings and processes – an echo of life’s origins, perhaps. It might help us understand how life on Earth began, or even inspire strategies to build tiny computers.

The Game of Life is the best-known example of a cellular automaton, in which patterns form and evolve on a grid according to a few simple rules. You play the game by choosing an initial pattern of “live” cells, and then watch as the configuration changes over many generations as the rules are applied over and over again (see “Take two simple rules”).

The rules of the game were laid down by mathematician John Conway in 1970, but cellular automata first took off in the 1940s when the late mathematician John von Neumann suggested using them to demonstrate self-replication in nature. This lent philosophical undertones to Life, which ended up attracting a cult following.

Life enthusiasts have since catalogued an entire zoo of interesting patterns, such as “spaceships” that travel across the grid, or “guns”, which constantly spawn other patterns. But a pattern that spawned an identical copy of itself proved elusive.

New Scientist:

(Thanks socialfiction)

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