Then Again, Maybe It's Me

May 23

If Cable Is Dying, Why Is It Still Making So Much Money? -

futuristgerd:

But the cable companies aren’t exclusively in the business of selling TV. They’re really in the business of communications infrastructure, which is TV, phone, and Internet. The Internet business in particular has done very well for them. Since cable video subs peaked in the late 1990s, the industry has added 45 million high-speed Internet customers (SNL Kagan data, again).

“Gerd Leonhard will talk on ‘The Future of Business and Communications in a Networked Society’ focusing on how “SoLoMo” - social local mobile technology is changing the way in which we obtain, digest and use information and what this, in the context of global economic forces, means for communications, business and human relationships.” — GBTA announces opening keynote speaker at GBTA Europe Conference 2013 in Prague (via futuristgerd)

May 21

nevver: “There is nothing more provocative than minding your own business.”

nevver:

“There is nothing more provocative than minding your own business.”

“Why the hell do I have to keep updating apps on my iPhone?” — John McCain to Tim Cook (via digg)

“One of the greatest threats we face is, simply put, bullshit. We are drowning it. We are drowning in partisan rhetoric that is just true enough not to be a lie; in industry-sponsored research; in social media’s imitation of human connection; in legalese and corporate double-speak. It infects every facet of public life, corrupting our discourse, wrecking our trust in major institutions, lowering our standards for the truth, making it harder to achieve anything.” — Jon Lovett’s commencement address to Pitzer College. (via theatlantic)

[video]

thisistheverge: The Xbox One will always be listening to you, in your own home Did Microsoft just invent the Telescreen from ‘1984?’

thisistheverge:

The Xbox One will always be listening to you, in your own home

Did Microsoft just invent the Telescreen from ‘1984?’

[video]

pewresearch: JUST RELEASED: Teens, Social Media and Privacy Our new report looks at sharing habits, privacy settings and network size for teens on social media. What do you share?

pewresearch:

JUST RELEASED: Teens, Social Media and Privacy

Our new report looks at sharing habits, privacy settings and network size for teens on social media. What do you share?

A demographic portrait of Twitter, Tumblr, Pinterest, Instagram and Facebook users -

analyticisms:

Great demographic breakdown of the major social networks. Must-read for social media marketers.

nevver: Graduate

nevver:

Graduate

analyticisms: Great infographic from the ever reliable Pew Center. pewinternet: Teens are sharing more personal information on their profiles than in the past. They choose private settings for Facebook, but share with large networks of friends. 60% of teen Facebook users keep their profiles private. Brand spanking new report out today on teens and their digital lives. Teen twitter use has grown substantially; 24% of teens use twitter, up from 16% in 2011. But Facebook is still most popular. This infographic says it all, but stop by the report for the nitty gritty. http://pewrsr.ch/191zI4V

analyticisms:

Great infographic from the ever reliable Pew Center.

pewinternet:

Teens are sharing more personal information on their profiles than in the past. They choose private settings for Facebook, but share with large networks of friends. 60% of teen Facebook users keep their profiles private.

Brand spanking new report out today on teens and their digital lives. Teen twitter use has grown substantially; 24% of teens use twitter, up from 16% in 2011. But Facebook is still most popular. This infographic says it all, but stop by the report for the nitty gritty. http://pewrsr.ch/191zI4V

neurosciencestuff: Complex brain function depends on flexibility Over the past few decades, neuroscientists have made much progress in mapping the brain by deciphering the functions of individual neurons that perform very specific tasks, such as recognizing the location or color of an object. However, there are many neurons, especially in brain regions that perform sophisticated functions such as thinking and planning, that don’t fit into this pattern. Instead of responding exclusively to one stimulus or task, these neurons react in different ways to a wide variety of things. MIT neuroscientist Earl Miller first noticed these unusual activity patterns about 20 years ago, while recording the electrical activity of neurons in animals that were trained to perform complex tasks. “We started noticing early on that there are a whole bunch of neurons in the prefrontal cortex that can’t be classified in the traditional way of one message per neuron,” recalls Miller, the Picower Professor of Neuroscience at MIT and a member of MIT’s Picower Institute for Learning and Memory. In a paper appearing in Nature on May 19, Miller and colleagues at Columbia University report that these neurons are essential for complex cognitive tasks, such as learning new behavior. The Columbia team, led by the study’s senior author, Stefano Fusi, developed a computer model showing that without these neurons, the brain can learn only a handful of behavioral tasks. “You need a significant proportion of these neurons,” says Fusi, an associate professor of neuroscience at Columbia. “That gives the brain a huge computational advantage.” Lead author of the paper is Mattia Rigotti, a former grad student in Fusi’s lab. Multitasking neurons Miller and other neuroscientists who first identified this neuronal activity observed that while the patterns were difficult to predict, they were not random. “In the same context, the neurons always behave the same way. It’s just that they may convey one message in one task, and a totally different message in another task,” Miller says. For example, a neuron might distinguish between colors during one task, but issue a motor command under different conditions. Miller and colleagues proposed that this type of neuronal flexibility is key to cognitive flexibility, including the brain’s ability to learn so many new things on the fly. “You have a bunch of neurons that can be recruited for a whole bunch of different things, and what they do just changes depending on the task demands,” he says. At first, that theory encountered resistance “because it runs against the traditional idea that you can figure out the clockwork of the brain by figuring out the one thing each neuron does,” Miller says. For the new Nature study, Fusi and colleagues at Columbia created a computer model to determine more precisely what role these flexible neurons play in cognition, using experimental data gathered by Miller and his former grad student, Melissa Warden. That data came from one of the most complex tasks that Miller has ever trained a monkey to perform: The animals looked at a sequence of two pictures and had to remember the pictures and the order in which they appeared. During this task, the flexible neurons, known as “mixed selectivity neurons,” exhibited a great deal of nonlinear activity — meaning that their responses to a combination of factors cannot be predicted based on their response to each individual factor (such as one image). Expanding capacity Fusi’s computer model revealed that these mixed selectivity neurons are critical to building a brain that can perform many complex tasks. When the computer model includes only neurons that perform one function, the brain can only learn very simple tasks. However, when the flexible neurons are added to the model, “everything becomes so much easier and you can create a neural system that can perform very complex tasks,” Fusi says. The flexible neurons also greatly expand the brain’s capacity to perform tasks. In the computer model, neural networks without mixed selectivity neurons could learn about 100 tasks before running out of capacity. That capacity greatly expanded to tens of millions of tasks as mixed selectivity neurons were added to the model. When mixed selectivity neurons reached about 30 percent of the total, the network’s capacity became “virtually unlimited,” Miller says — just like a human brain. Mixed selectivity neurons are especially dominant in the prefrontal cortex, where most thought, learning and planning takes place. This study demonstrates how these mixed selectivity neurons greatly increase the number of tasks that this kind of neural network can perform, says John Duncan, a professor of neuroscience at Cambridge University. “Especially for higher-order regions, the data that have often been taken as a complicating nuisance may be critical in allowing the system actually to work,” says Duncan, who was not part of the research team. Miller is now trying to figure out how the brain sorts through all of this activity to create coherent messages. There is some evidence suggesting that these neurons communicate with the correct targets by synchronizing their activity with oscillations of a particular brainwave frequency. “The idea is that neurons can send different messages to different targets by virtue of which other neurons they are synchronized with,” Miller says. “It provides a way of essentially opening up these special channels of communications so the preferred message gets to the preferred neurons and doesn’t go to neurons that don’t need to hear it.”

neurosciencestuff:

Complex brain function depends on flexibility

Over the past few decades, neuroscientists have made much progress in mapping the brain by deciphering the functions of individual neurons that perform very specific tasks, such as recognizing the location or color of an object.

However, there are many neurons, especially in brain regions that perform sophisticated functions such as thinking and planning, that don’t fit into this pattern. Instead of responding exclusively to one stimulus or task, these neurons react in different ways to a wide variety of things. MIT neuroscientist Earl Miller first noticed these unusual activity patterns about 20 years ago, while recording the electrical activity of neurons in animals that were trained to perform complex tasks.

“We started noticing early on that there are a whole bunch of neurons in the prefrontal cortex that can’t be classified in the traditional way of one message per neuron,” recalls Miller, the Picower Professor of Neuroscience at MIT and a member of MIT’s Picower Institute for Learning and Memory.

In a paper appearing in Nature on May 19, Miller and colleagues at Columbia University report that these neurons are essential for complex cognitive tasks, such as learning new behavior. The Columbia team, led by the study’s senior author, Stefano Fusi, developed a computer model showing that without these neurons, the brain can learn only a handful of behavioral tasks.

“You need a significant proportion of these neurons,” says Fusi, an associate professor of neuroscience at Columbia. “That gives the brain a huge computational advantage.”

Lead author of the paper is Mattia Rigotti, a former grad student in Fusi’s lab.

Multitasking neurons

Miller and other neuroscientists who first identified this neuronal activity observed that while the patterns were difficult to predict, they were not random. “In the same context, the neurons always behave the same way. It’s just that they may convey one message in one task, and a totally different message in another task,” Miller says.

For example, a neuron might distinguish between colors during one task, but issue a motor command under different conditions.

Miller and colleagues proposed that this type of neuronal flexibility is key to cognitive flexibility, including the brain’s ability to learn so many new things on the fly. “You have a bunch of neurons that can be recruited for a whole bunch of different things, and what they do just changes depending on the task demands,” he says.

At first, that theory encountered resistance “because it runs against the traditional idea that you can figure out the clockwork of the brain by figuring out the one thing each neuron does,” Miller says.

For the new Nature study, Fusi and colleagues at Columbia created a computer model to determine more precisely what role these flexible neurons play in cognition, using experimental data gathered by Miller and his former grad student, Melissa Warden. That data came from one of the most complex tasks that Miller has ever trained a monkey to perform: The animals looked at a sequence of two pictures and had to remember the pictures and the order in which they appeared.

During this task, the flexible neurons, known as “mixed selectivity neurons,” exhibited a great deal of nonlinear activity — meaning that their responses to a combination of factors cannot be predicted based on their response to each individual factor (such as one image).

Expanding capacity

Fusi’s computer model revealed that these mixed selectivity neurons are critical to building a brain that can perform many complex tasks. When the computer model includes only neurons that perform one function, the brain can only learn very simple tasks. However, when the flexible neurons are added to the model, “everything becomes so much easier and you can create a neural system that can perform very complex tasks,” Fusi says.

The flexible neurons also greatly expand the brain’s capacity to perform tasks. In the computer model, neural networks without mixed selectivity neurons could learn about 100 tasks before running out of capacity. That capacity greatly expanded to tens of millions of tasks as mixed selectivity neurons were added to the model. When mixed selectivity neurons reached about 30 percent of the total, the network’s capacity became “virtually unlimited,” Miller says — just like a human brain.

Mixed selectivity neurons are especially dominant in the prefrontal cortex, where most thought, learning and planning takes place. This study demonstrates how these mixed selectivity neurons greatly increase the number of tasks that this kind of neural network can perform, says John Duncan, a professor of neuroscience at Cambridge University.

“Especially for higher-order regions, the data that have often been taken as a complicating nuisance may be critical in allowing the system actually to work,” says Duncan, who was not part of the research team.

Miller is now trying to figure out how the brain sorts through all of this activity to create coherent messages. There is some evidence suggesting that these neurons communicate with the correct targets by synchronizing their activity with oscillations of a particular brainwave frequency.

“The idea is that neurons can send different messages to different targets by virtue of which other neurons they are synchronized with,” Miller says. “It provides a way of essentially opening up these special channels of communications so the preferred message gets to the preferred neurons and doesn’t go to neurons that don’t need to hear it.”

theatlantic: Just 27% of BA’s Have Jobs Related to Their Major? Don’t Believe the Fed’s New Stat Whenever you see a big, bold statistic about the fate of college grads, take it with a grain of salt. Read more. [Image: Federal Reserve]

theatlantic:

Just 27% of BA’s Have Jobs Related to Their Major? Don’t Believe the Fed’s New Stat

Whenever you see a big, bold statistic about the fate of college grads, take it with a grain of salt.

Read more. [Image: Federal Reserve]

May 10

Social networks will displace business processes, not socialize them - Stowe Boyd via GigaOM Research -

smarterplanet:

from the report’s Executive Summary

“Socialized business process” — the idea of adding social tools to traditional business processes — is unlikely to work in the long term. The enterprise is now transitioning to social network–based communication as introduced by social tools, and there is a fundamental conflict in communication models with business-process-centric business. The attempt to make the socialized business process work may be part of the adoption problem reported in the social-business industry.

The shift to social network’s pull communication, where individuals more or less subscribe to information sources, will run counter to business process push communication and eventually invalidate it. Push-and-pull communication styles won’t jibe, and pull lines up with the transition to social network–based communication. Most notably, this will undermine business processes and the collective-collaborative organization that evolved in parallel with business processes. The shift won’t take place in the way that email led to organizational flattening. Rather, it will invalidate the rules and roles of business processes and turn the process logic into just another kind of information passed along through the social network.

It may be obvious, but companies that are more oriented toward a connective-cooperative style of work will get more benefits from social networks than those that are less so. Stated more strongly, those wishing to get the boost that many believe is inherent in this lean, self-innovating, fast-and-loose model of work will have to actively move away from the cultural principles of slow-and-tight, twentieth-century business.

In order to better explore these rapidly changing dynamics, this report presents a psychodynamic cultural model for business called the 3C model. The name is based on three sorts of business culture:

We also explore various archetypes of individuals’ psychosocial matches with the various flavors of companies. The freelancer and follower archetypes, for example, do well in cooperative settings, but they are poorly matched with entrepreneurial organizations (which may explain Yahoo CEO Marissa Mayer’s recent edict excluding remote work.)

High-performing companies of the near future will be operating based on looser ties among individuals in and across businesses. Many more of them will be supported by next-generation cooperative tools. Individuals in these companies will have more autonomy, and there will be more opportunity seeking when compared to the largely slow-and-tight, risk-averse companies that are dominant today. The value of consensus is falling in a rapidly changing, unstable world where there is a higher premium for business innovation and more uncertainty than ever before. And this leads to a devaluation of business processes, in particular those business processes intended to direct human agency and to act as a surrogate for management directing employees’ every move.

You can sign up for a seven day free trial of the GigaOM Research service, and read the entire report.

(Source: stoweboyd, via emergentfutures)