AI News, Tendency of the rate of profit to fall artificial intelligence

Weekly Digest #9 [Success, Marketing Trends, Habits, Artificial Intelligence Spending]

Laws of Success: The first law says that performance drives success but when performance is not measurable, networks drive success.

The 4th law says that team success requires diversity and balance however a single individual will receive the credit for the group’s achievement.

Rather than opening up a marketing funnel that swallows whoever it can, businesses are starting to efficiently leverage content to target niche audiences.

These are little AI helpers integrated into websites that can answer questions and fulfill requests quickly and many can accomplish this without sacrificing personality.

It makes data analysis more efficient, can target potential leads rapidly and can perform tasks that humans struggle with.

Sometimes it takes the form of advanced machine learning, but even Netflix’s recommendation system that suggests new TV shows to watch is technically AI.

In an economy where people are rightfully cautious about hacks, leaks, and theft, they will favor establishments that can promise them the safest business experience.

They’re growing up in a scary world and a struggling economy, so they’re more likely to turn to companies that make the world a better place.

Google has long enabled reverse-image searches but new camera technology makes it possible for people to take a picture of something in the real world and find information about it.

Marketing is becoming increasingly complex, so it’s practical for marketers to keep their eyes on emerging technologies, methods and patterns.

Better Habits: Everyone wants to cultivate better habits, develop better accountability and a clearer vision for their life but few want to work to make those habits a reality.

If you wish to practice running in the morning, keeping a pair of running shoes besides your bed will help create stickiness.

Effective Business Models: Since businesses thrive on profit, one of the crucial questions you must ask yourself at the outset is how to grow your user base to build revenue.

Both of these issues are covered under the umbrella term “business model.” While a lot of business models exist, four of them are worth studying in the context of today’s marketplace.

Technology is considered to be its single major propeller, as technology serves as a fillip to its core pre-conditions, which include cost-effectiveness and speed.

It’s especially suitable for platform businesses that utilize already established an infrastructure to solve a problem and aids in scaling up.

The purpose of this model is to promote the basic features for free, where anyone/everyone would be able to use them, but grant only premium users access to the advanced ones.

This model works on a 5 percent rule — that is, 5 percent of paying customers support the remaining 95 percent of free users.

Consumers actually earn money when purchasing everyday items, such as paper towels, toilet paper, toothpaste, razors and so on.

If you’re going to create a widely appealing app or game, then this model is one that you’ll want to consider, as people will want to purchase virtual goods that make their experience with a fascinating product more fun.

This culture of looking successful drives a wicked cycle of consumption leading to high consumption lifestyles supplemented through high income, eventually causing erosion of the earned income.

The spending entitlement that creeps in our psyche after earning high incomes by spending money on education, working long hours and shouldering stress is detrimental to our finances.

ML replaces handwritten logical steps with automatically detected patterns in data and works much better for a very broad class of questions.

Some data would be proprietary and unique to the business which gives them the advantage some data might apply to a use case that is found in many companies and industries and some data would not be required as the product would have already started functioning smoothly.

Diffusion also results in all types of startups that can build things pretty quickly Follow us on twitter @GlanceThrough for daily tweet summaries of articles we find interesting The link to the original articles is hyperlinked in the title of each summary.

Third Text

The article begins with a brief discussion of the 2018 Italian elections, which resulted in institutional crisis first, and immediately after in the formation of a populist government.

From there, it tackles the global rise of contemporary populism as a symptom of our post-political unwillingness, or inability, to confront the fetishistic core of the capitalist valorisation dynamic, which has long encountered its historical limit and is currently languishing in a state of terminal crisis.

Ethics of artificial intelligence

The ethics of artificial intelligence is the part of the ethics of technology specific to robots and other artificially intelligent beings.

divided into roboethics, a concern with the moral behavior of humans as they design, construct, use and treat artificially intelligent beings, and machine ethics, which is concerned with the moral behavior of artificial moral agents (AMAs).

It has been suggested that robot rights, such as a right to exist and perform its own mission, could be linked to robot duty to serve human, by analogy with linking human rights to human duties before society.[3]

Pamela McCorduck counters that, speaking for women and minorities 'I'd rather take my chances with an impartial computer,' pointing out that there are conditions where we would prefer to have automated judges and police that have no personal agenda at all.[14]

However, Kaplan and Haenlein stress that AI systems are only as smart as the data used to train them since they are, in their essence, nothing more than fancy curve-fitting machines: Using AI to support a court ruling can be highly problematic if past rulings show bias toward certain groups since those biases get formalized and engrained, which makes them even more difficult to spot and fight against.[15]

'If any major military power pushes ahead with the AI weapon development, a global arms race is virtually inevitable, and the endpoint of this technological trajectory is obvious: autonomous weapons will become the Kalashnikovs of tomorrow', says the petition, which includes Skype co-founder Jaan Tallinn and MIT professor of linguistics Noam Chomsky as additional supporters against AI weaponry.[29]

Regarding the potential for smarter-than-human systems to be employed militarily, the Open Philanthropy Project writes that these scenarios 'seem potentially as important as the risks related to loss of control', but that research organizations investigating AI's long-run social impact have spent relatively little time on this concern: 'this class of scenarios has not been a major focus for the organizations that have been most active in this space, such as the Machine Intelligence Research Institute (MIRI) and the Future of Humanity Institute (FHI), and there seems to have been less analysis and debate regarding them'.[30]

To account for the nature of these agents, it has been suggested to consider certain philosophical ideas, like the standard characterizations of agency, rational agency, moral agency, and artificial agency, which are related to the concept of AMAs.[35]

In 2009, during an experiment at the Laboratory of Intelligent Systems in the Ecole Polytechnique Fédérale of Lausanne in Switzerland, robots that were programmed to cooperate with each other (in searching out a beneficial resource and avoiding a poisonous one) eventually learned to lie to each other in an attempt to hoard the beneficial resource.[39]

In 2009, academics and technical experts attended a conference organized by the Association for the Advancement of Artificial Intelligence to discuss the potential impact of robots and computers and the impact of the hypothetical possibility that they could become self-sufficient and able to make their own decisions.

They noted that some machines have acquired various forms of semi-autonomy, including being able to find power sources on their own and being able to independently choose targets to attack with weapons.

In a paper on the acquisition of moral values by robots, Nayef Al-Rodhan mentions the case of neuromorphic chips, which aim to process information similarly to humans, nonlinearly and with millions of interconnected artificial neurons.[47]

Inevitably, this raises the question of the environment in which such robots would learn about the world and whose morality they would inherit - or if they end up developing human 'weaknesses' as well: selfishness, a pro-survival attitude, hesitation etc.

Wendell Wallach and Colin Allen conclude that attempts to teach robots right from wrong will likely advance understanding of human ethics by motivating humans to address gaps in modern normative theory and by providing a platform for experimental investigation.

Nick Bostrom and Eliezer Yudkowsky have argued for decision trees (such as ID3) over neural networks and genetic algorithms on the grounds that decision trees obey modern social norms of transparency and predictability (e.g.

while Chris Santos-Lang argued in the opposite direction on the grounds that the norms of any age must be allowed to change and that natural failure to fully satisfy these particular norms has been essential in making humans less vulnerable to criminal 'hackers'.[40]

Many researchers have argued that, by way of an 'intelligence explosion' sometime in the 21st century, a self-improving AI could become so vastly more powerful than humans that we would not be able to stop it from achieving its goals.[50] In

However, instead of overwhelming the human race and leading to our destruction, Bostrom has also asserted that super-intelligence can help us solve many difficult problems such as disease, poverty, and environmental destruction, and could help us to “enhance” ourselves.[52]

Unless moral philosophy provides us with a flawless ethical theory, an AI's utility function could allow for many potentially harmful scenarios that conform with a given ethical framework but not 'common sense'.

Amazon, Google, Facebook, IBM, and Microsoft have established a non-profit partnership to formulate best practices on artificial intelligence technologies, advance the public's understanding, and to serve as a platform about artificial intelligence.

They stated: 'This partnership on AI will conduct research, organize discussions, provide thought leadership, consult with relevant third parties, respond to questions from the public and media, and create educational material that advance the understanding of AI technologies including machine perception, learning, and automated reasoning.'[54]

The same idea can be found in the Emergency Medical Hologram of Starship Voyager, which is an apparently sentient copy of a reduced subset of the consciousness of its creator, Dr. Zimmerman, who, for the best motives, has created the system to give medical assistance in case of emergencies.

This event caused an ethical schism between those who felt bestowing organic rights upon the newly sentient Geth was appropriate and those who continued to see them as disposable machinery and fought to destroy them.

2019 Global Health Care Outlook

Health care stakeholders—providers, governments, payers, consumers, and other companies/organizations—struggling to manage clinical, operational, and financial challenges envision a future in which new business and care delivery models, aided by digital technologies, may help to solve today’s problems and to build a sustainable foundation for affordable, accessible, high-quality health care.

This vision may have a greater probability of becoming a reality if all stakeholders actively participate in shaping the future— by way of shifting focus away from a system of sick care in which we treat patients after they fall ill, to one of health care which supports well-being, prevention, and early intervention.

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