Technology allowing our thoughts and feelings to be translated into a digital form – and shared – is already a reality. Brain computer interfaces (BCI) allow us to connect our minds to computers for some limited purposes, and big tech companies including Facebook and many startups want to make this technology commonplace. The AI and ML deployments are well underway, but for CXOs the biggest issue will be managing these initiatives, and figuring out where the data science team fits in and what algorithms to buy versus build. For those of you terrified by the prospect of technology recording – and broadcasting – your opinions of the boss, your secret fears, or anything else – relax. BCIs are currently not sophisticated enough to collect such granular information.
Policies are the foundation for any successful organization. Policies are the rules, or laws, of an organization. Heck, one could argue that an organization's culture is better defined by its policies than it is by the character of its leadership team. Unfortunately, the management, creation and execution of policies haven't changed much since the days of "time-and-motion studies". In many cases, policies are nothing more than a static list of what-if rules that govern what workers are to do in well-defined situations.
Artificial Intelligence is poised to disrupt many industries, but education arena has not typically been at the forefront of such conversations. If it has been included at all, the narrative has been in a more abstract manner than actual application. And even though several companies such as Carnegie Learning and Content Technologies, Inc have taken either more adult learning approaches or those that are deeply rooted in tech, the space is still anyone's game with new trends to be developed for Gen Z. The industry is an important one not only for its ability to generate an entirely new level of learning but also because of the very real business opportunity in the space. Indeed, the artificial intelligence in education size is forecasted at a market size worth $6 billion dollars by 2024.
Can patents be issued for technology or algorithms derived by artificial intelligence? That's a problem that lawyers and researchers are now grappling with. Law firm Baker McKenzie predicts that "patentability of AI-created inventions, liability for infringement by AI, and patent subject-matter eligibility of AI technologies are the top three areas of patent law that will be disrupted by AI." Kay Firth-Butterfield, Head of AI and ML at the World Economic Forum Center, said that "we are about to witness a collision between artificial intelligence and various aspects of patent law. This technology is going to change the game for many sectors, and will impact numerous regulations and legal fields." Currently patents are awarded to individuals.
With damage related to cybercrime projected to hit $6 trillion annually by 2021, enterprises are putting more emphasis than ever on securing their digital and organizational assets. While rudimentary machine learning has played a role in cyber threats for some years, today there's talk of the looming threat of malicious AI: AI-powered cyber-attacks capable of causing massive damage worldwide without the involvement of human operators. To better understand the threats and opportunities presented by AI in the cyber security space, we went to the AI Summit San Francisco to catch up with Justin Fier, director of cyber intelligence and analytics at Darktrace – the company putting AI to work on cyber defense. Justin's background is in the US intelligence community, and today works with Darktrace's global customers on threat analysis, defensive cyber operations, IoT security, and machine learning. What are the key takeaways from your AI Summit keynote?
The economic numbers from China are pointing to the realities of the trade war – a slowing China's economy. Results of Published Model Trades for THU 10/17 Find below the detailed outcome tracking of our models' trading plans for the day, as well as the results for the last month. Note: Our daily "S&P 500 Outlook, Forecast, and Trading plan" will be posted around 9:00am EDT, every trading day. Overnight futures markets are cheering the last minute deal struck between the UK and the EU on Brexit, despite serious doubts whether the UK parliament would approve the deal. Results of Published Model Trades for WED 10/16 Find below the detailed outcome tracking of our models' trading plans for the day, as well as the results for the last month.
If Facebook and Elon Musk's ambitions to directly connect human brains to machines are any indication, it seems we will become increasingly dependent on smart devices. Less bombastic than this proposal, but already widespread, are more mundane forms of augmentation – neural prostheses allow brains to control replacement body parts, artificial organs can be designed to specific bodies, and embedded devices like insulin pumps can intelligently support their hosts. With this is mind, we asked six experts the following question: How will technologically augmenting humans affect sustainability? The implications of human augmentation are so complex that it is difficult to succinctly assess what their implications will be for sustainability. There are, of course, potential benefits.
Over this past summer, I was fortunate enough to be given the opportunity to deliver a speech to the State University of New York (SUNY) College of Optometry residency class of 2019. During this 20 minutes (which they likely perceived as just over an hour), I recommended that residents take a few moments and conduct a search of the world's literature using the key words "deep learning" with the disease of their choice. Conducting such a search myself gave me a better understanding of the likely direction of health care in my clinical lifetime. A study recently published in JAMA Ophthalmology describes a deep learning system which appears to show high sensitivity and specificity for the detection of glaucoma.1 Previously by Dr. Casella: Consider IOP fluctuations when diagnosing glaucoma Deep learning So, just what exactly is deep learning? In the arena of artificial intelligence, this subset of machine learning is based on so-called "neural networks" that process data into concepts.
Every year, around 50,000 individuals graduate to become certified doctors. In order to maintain the minimum doctor-patient ratio, as suggested by WHO, India will need 2.3 Mn doctors by 2030. If there was ever a requirement to push healthcare in India into the future, it is now! Today is the time when we can see significant disruption in the Indian healthcare industry. Much of this is credited to the level of involvement of artificial intelligence, big data, cloud, machine learning and deep learning, and wearables or fitness trackers which are connecting the organizations with the individuals.