Category Archives: Artificial Intelligence
Top Artificial Intelligence Books Released In 2019 That You Must Read – Analytics India Magazine
Artificial Intelligence has had many breakthroughs in 2019. In fact, we can go as far as to say that it has trickled down to every single facet of modern life. With its intervention in our daily life, it is imperative that everyone knows about how it is affecting our lives, bringing about change in it, the threats and possible solutions.
While there are some people who still think AI is only robots and chatbots, it is important that they know of the advancements in the field. There are many online courses and books on artificial intelligence that give a comprehensive understanding to the reader whether it is a professional or an AI enthusiast.
In this article, we have compiled a list of books on artificial intelligence published in 2019 that one can use to learn more about this fascinating technology:
Written by Dr Eric Topol, an American cardiologist, geneticist and digital medicine researcher, Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again, is Amazon #1 bestseller this year.
This book boldly sets out the potential of AI in healthcare and deep medicine. Topol calls AI the next industrial revolution. The book contains short examples to highlight AIs importance along with a proper expansion on likely AI is going to transform the medical industry. Topol believes that AI can not only help in enhancing diagnosis and treatment but also help them in saving time in other activities like taking notes, reading scans which will eventually help them to spend more time on the patients. This is a resourceful book for someone interested in AI and its impact on healthcare.
Written by Dr Stuart Russell, Human Compatible: AI and the Problem of Control is possibly one of the most important books of this year on AI. The book talks about the threats by artificial intelligence and solutions to it. The author, Stuart Russell, makes use dry humour not to make his book sound like a boring information magazine.
The book is for both the public and AI researches, Stuart Russel, in this doesnt hammer AI, he points out the threats and solution as someone who feels a sense of responsibility towards the changes and revolution his own field is bringing.
This book is written by Marcus du Sautoy, a professor of mathematics at the University of Oxford and a researcher fellow at the Royal Society.
This book is a fact-packed, funny journey to the world of AI. It questions the present meaning of the word creativity and about how the machine will be able to crack the code on human emotions.
This book dances around the concept of using AI assistance in art-making. The book discusses the math behind ML and AI as its centre point of discussion in art.
Janelle Shanes AIwierdness.com is an AI humour blog and looks to have a different take on AI, the part of AI. In this book, the author makes use of humorous cartoons and pop-culture illustrations to try and take a look inside the algorithms that are used in machine learning.
The authors of this book Gary Marcus, a scientist and the founder and CEO of Robust.AI and Ernest Davis, a professor of computer science at NYU tell what AI is, what it is not, its potentials if we worked towards it with more resilience and be more creative. Many authors seem to hype up AI, not just the good part about it but also the wrong side about it. The authors here seem to have found the balance in between.
The book, Rebooting AI: Building Artificial Intelligence We Can Trust, highlights the weaknesses of the current technology, where it is going wrong and what should we be doing to find the solutions. It isnt just some book that only researchers can read but also for the general public. It illustrates many examples and excellent use of humour wherever needed.
The first edition of the series of books written by the Alex Castrounis, answer one of the most critical questions in todays age concerning business and AI, How can I build a successful business by using AI?
The AI for People and Business: A Framework for Better Human Experiences and Business Success is exclusively written for anyone interested in making use of AI in their organisation.
The author examines the value of Ai and gives solutions for developing an AI strategy that benefits both people and businesses.
This book by Andriy Burkov remains true to its name and just manages to do the seemingly impossible task of trying to bundle all of the machine learning inside of a hundred-page book.
This book provides an in-depth introduction to the field of machine learning with the smart choice of topics for both theory and practice.
If you are new to the field of machine learning, then this book gives you a comprehensive introduction to the vocabulary/ terminology.
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Top Artificial Intelligence Books Released In 2019 That You Must Read - Analytics India Magazine
Artificial intelligence must be used with care – The Australian Financial Review
When AI goes into the machine learning space, it opens up a range of issues such as biases and privacy, she says. Boards have to be switched on to this and be able to ask the right questions.
According to Williams, a significant proportion of the challenges caused by AI usage within companies comes from the fact that the technology is far from transparent. Even the people who build it dont really know why it does what it does, she says. The board is critical. If it is successfulin understanding AI, developing strategies for it, and integrating it into mainstream business strategy, the payoff is huge.
Asked to nominate other technology-related issues occupying the minds board members, panel members pointed to a range including security and the ability to withstand cyber attacks.
Cyber security is really at the top of the list, says David Attenborough, managing director and chief executive at betting company Tabcorp. This is because any company is under permanent attack from different directions and you need to be protecting your customers, your networks and youremployees from those attacks.
The other major issue that keeps me awake at night is the resilience of networks because we have multiple systems supporting a massive retail network and a big digital network. On big days, such as the Melbourne Cup, if you have a system that goes down it is incredibly expensive and disruptiveand reputationally damaging.
David Attenborough, managing director and chief executive at betting company Tabcorp, says cyber security is top priority.Jesse Marlow
While information technology is a critical component for organisations of all sizes, the panellists also stressed that Australian businesses must be more than simply technology consumers.
To achieve long-term growth, it is vital to deploy new technologies to underpin sustained and far-reaching innovation.
The board wants too see a pipeline of ideas, says Stops. They want to know that the company is constantly thinking about new ways to do things and that the pipeline is constantly being filled and fed through.
She says innovation is not something that is unique to a particular group. Rather, it has to be a mindset and something that is in place right across an organisation.
The usual approach within a lot of companies has been to carve off a group and call it an innovation team, she says. Companies are now realising that this is not creating an innovation culture - its just putting some smart people in a corner.
Stops warns, however, that its important how innovation and new ideas are handled. Care needs to be taken that it doesnt get caught up in traditional multi layers of approval which can lead to a good idea dying before it can be fully developed.
The board should be keen to make sure there is a way in which those ideas can move through the organisation quite quickly, she says.
Also, there is a need to create a culture in which it is OK to fail. A lot of organisations spend money on innovation and new ideas and if they dont work people are shot and off they go. That is not what an innovation culture is all about.
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Artificial intelligence must be used with care - The Australian Financial Review
Ume University: Master all areas of Artificial Intelligence – Study International News
Artificial intelligence (AI) is transforming work and life as we know it, already boosting workplace efficiency and leading to noticeable improvements to the quality of for instance healthcare, lowering costs while giving clinicians time to work with their patients more closely, and with more insight. This was made clear in arecent MIT Technology Review Insights surveyproduced in partnership with GE Healthcare, where more than 82 percent of healthcare business leaders said their AI deployments were showing positive results across operational and administrative activities,.
When analysing the impact AI would have on the global education sector, founders of theInstitute for Ethical AI in Education (IEAIED) said there wasno need to fear the technology. Rather than replace the human element in education, AI would augment teaching and learning, they said.
There are highly beneficial applications of machine learning inside the area of education. Artificial Intelligence may enable personalised learning, especially important for students with specialized needs and challenges. Awell-designed AI can be used to identify learners particular needs so that everyone especially the most vulnerable can receive targeted support.
With global education and healthcare being just two of many sectors that AI has advanced so far, and withhundreds more AI technology developmentson the horizon, such as autonomous vehicles, manufacturing and financial services to add to the list, the need for expertise in the field appears limitless!
Firmly supporting this need and accepting this challenge is theFaculty of Science and TechnologyatUme University, Sweden.
Currently open forautumn 2020 intake, their newMasters in Artificial Intelligenceis a postgraduate programme that enables you to develop broad and core competence in AI and equips you with the digital tools necessary for future career success.
Youll also experience a combination of lectures, seminars, group work, and tutorials in conjunction with different types of assignments and laboratory work to advance your AI education in a multidisciplinary manner.
It is of critical importance to study in a more multidisciplinary manner, where humanities and social sciences are combined with science and technology. AI can no longer be seen as a purely technical or computer science discipline. It is per definition interdisciplinary, says Ume Department of Computing Science Professor, Virginia Dignum.
One of the first professors recruited to Sweden as part of the Wallenberg AI, Autonomous Systems and Software Program (WASP) initiative and actively involved in several international initiatives on policy and strategy guidelines for AI research and applications, such as theEuropean Commission High Level Expert Group on Artificial Intelligence (AI HLEG), Dignum is one of the AI experts at Ume who are driving research and graduate success forward.
My position at Ume University makes it possible for me to look at societal, ethical and cultural consequences of AI. I will for instance be studying methods and tools to ensure that AI systems are formed not to violate human values and ethical principles, says Dignum, who also leads the research group Social and Ethical Artificial Intelligence at the Faculty.
Another integral member at the Faculty is Senior Lecturer Helena Lindgren.
Understanding the urgency of AI integration, Lindgren believes that the university needs to be driven to produce research that develops, educates and enhances the capabilities of AI in society, both in terms of system development and implementation.
One of the objectives at Ume is to raise societys AI competence, such as through continuing education and professional development of currently employed persons. Its very important for Sweden as a nation, as well as its companies and organisations, to be able to take the next step in digital development, says Lindgren.
Lindgren and Dignum reflect the high caliber of the 30-strong researchers at Ume University that are engaged in the development of AI in different areas.
To study here is to be under their expert guidance as you undertake courses that relate to human-AI interaction and complete student projects conducted in collaboration with an organisation addressing societal challenges.
In these projects, students are expected to collaborate in interdisciplinary teams and with representatives from industry and public organisations, adding a practical twist to the 2020 course.
In this English-taught Masters, you are also expected to take full responsibility for organising your tasks so that deadlines are met and collaborative work within student projects are manageable within office hours.
Despite being a new course, AI is not a new focus for Ume.
In the 1970s, Ume Professor Lars-Erik Janlert focused on Knowledge Representation, and in the early 1980s he formed the Swedish AI Society together with other Swedish researchers.
Since then, Ume has expanded its outreach into a variety of research and education activities across different departments and faculties and is now one of seven universities that are part of the governmental initiative AI Competence for Sweden.
Ume University
Continuously building its research efforts through its strong interdisciplinary traditions and close collaborations with society, AI@UmU initiatives have also established an expanding network of researchers, teachers, students and professionals who want to learn, discuss and collaborate around AI-related issues via seminars, panel discussions and courses.
Always welcome to discuss the latest tech revelations and AI advancements with their professors and visiting professionals, Ume students are motivated to unearth AI research angles of their own.
From day one of the new Masters programme, theyll deepen their insight into this exciting field and take their knowledge of AIs theoretical foundations, intelligent robotics, machine learning and data science further.
So, if youre ready to master all areas of AI and want to start your postgraduate study venture in Sweden, click here to find out about the application and eligibility process.
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Ume University: Master all areas of Artificial Intelligence - Study International News
Wearable Artificial Intelligence (AI) Competitive Market Status,Outlook, Trend and Forecast to 2026 – Media Releases – CSO Australia
In the global report, the wearable artificial intelligence (AI) competitive market outlook section mainly encompasses the fundamental dynamics of the market which include drivers, restraints, opportunities, and challenges faced by the industry. Drivers and restraints are intrinsic factors whereas opportunities and challenges are extrinsic factors of the market.
According to ARC, the global wearable artificial intelligence (AI) competitive market is expected to reach the market value of around $185 billion by 2026 and is expected to grow at a CAGR of around 27% in terms of revenue during the period 2019 - 2026. The report provides analysis of global Wearable Artificial Intelligence (AI) market for the period 2015-2026, wherein 2019 to 2026 is the forecast period and 2018 is considered as the base year.
A technologically sophisticated drug delivery system or instrument implanted below the skin for steady administration of medication or fluid is an implantable pump. These pumps are used for the supply of anti - spasmodic, chemotherapeutic and opioid medicines.
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The key drivers for development will be increased demand for AI assistants, increased operations in the Healthcare industry, the emergence of IoT and the integration of wireless technologies and the growth of wearable component technology.
As the majority of intelligent wearable equipment lacks basic safety mechanisms, an increasing concern for data security in smarts is preventing the growth of the wearable artificial intelligent market. Moreover, the cost of production is high and the consumption of batteries is limited.
Segmentation Outlook
In the forecast period, the earwear market is projected to grow at more than 43 percent. The increasing integration of AI-based voices like Siri and Alexa into the product range by large smartphone manufacturers drives the wearable artificial intelligence (AI) market. The growing popularity of AI-based voice helpers has led to firms like Bragi starting their own intelligent earwears using AI-based voice support to help users conduct different activity using voice commands. Most earwears have biosensors that track the heartbeats of the user and adapt different user experiences. For example, it individualizes soundtracks based on the heart rate of the users. The removal of 3.5 mm jack from smartphones and the increased integration of Bluetooth technology as a solution for traditional wired technology are another catalyst for the adoption of AI-based earwear devices.
Key Players & Strategies
The Wearable Artificial Intelligence (AI) market is consolidated with large number of manufacturers. The company profiling of key players in the market includes major business strategies, company overview and revenues. The key players of the market are Facebook, Apple, Samsung, Garmin, Fossil, Microsoft, HTC, Huawei, Bragi, Jabra, ANTVR, Huami and Google.
Large players like Huawei, Samsung, Facebook, Apple, Fitbit and Microsoft lead the wearable AI market. Large companies are currently working to develop cost-effective solutions to compete with Asia-Pacific regional actors. The tech players have worked with luxury brands to compete better in developing their own premium smartwatch product line with the large watch companies. Apple partnered with Nike and Herms in September 2016, for example, to develop its own premium smart clock offering range. Startups such as Misfit and ANTVR focus on the cost-effective supply of products to take advantage of the large players on the market.
Market Segment Analysis:
Acumen Research report focuses on market attractiveness by assessing the key market segments. The report also combines region-wise segments for a better understanding of the supply and demand ratio of this market. This exclusive study of the report analyzes the present and future market scenario and the industry trends that are influencing the growth of the segments. Besides, the report also covers the value chain analysis, supply chain analysis, and year-on-year basis analysis of this market.
Market Segmentation
Market, by Product
Market, by Application
Market Regional Analysis:
Based on the regions, the global wearable artificial intelligence (AI) competitive market is segmented into -North America (US and Canada), Europe (UK, Germany, France, Spain and Rest of Europe), Asia-Pacific (China, Japan, India, Australia, South Korea and Rest of Asia-Pacific), Latin America (Mexico, Brazil and Rest of Latin America), Middle East & Africa (GCC, South Africa and Rest of MEA).
The market research study on Wearable Artificial Intelligence (AI) Market (By Product: Fitness Band & Smartwatch, Head Mounted Display, Earwear; By Application: Consumer Electronics, Enterprise, Gaming) - Global Industry Analysis, Market Size, Opportunities and Forecast, 2019 - 2026 offers detailed insights on global Wearable Artificial Intelligence (AI) market segments with market dynamics and their impact. The report also covers basic technology development policies.
The report offers an overview of the market and statistical diagrams to support the expected figures. Our analysts predict the market scope and future prospects in an insightful way. The Acumen Research and Consulting report contains a comprehensive analysis of the global market in Wearable Artificial Intelligence (AI) segmented by molecular type, test type and region. The report outlines numerous growth strategies implemented by companies as well as the latest market trends. The market share and current position of all leading players are discussed in detail. It analyzes players ' new revenue sources and highlights the different strategies.
Key Questions Answered in the Report
The report addresses key questions concerning the market evolution and overarching trends shaping global market growth. Some of the key questions answered in the report include-
- What is the overall structure of the market?- What was the historical value and what is the forecasted value of the market?- What are the key product level trends in the market?- What are the market level trends in the market?- Which of the market players are leading and what are their key differential strategies to retain their stronghold?- Which are the most lucrative regions in the market space?
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Artificial intelligence will only improve over the next decade – KFI AM 640
The past ten years have seen a rise in artificial intelligence, from smart speakers and other devices to driverless cars. We're "not there yet" on either, but the next ten years should see an evolution of these technologies.
Rice engineering Professor Patrick Rodi says truly driverless cars may come to other countries first.
"Where the litigation environment is a bit different, so you don't have the tort law and the other legal ramifications and environments we have in this country."
Professor Rodi says Alexa and Siri will get better in the ten years.
"I don't see a huge revolution coming; I think Alexa is going to be smarter and predict your needs better and get to know the family a little bit better."
Professor Rodi says we've come a long way. 120 years ago we had very little technology, now we're trying to go to Mars.
"I think it's a wonderful time to be alive; I always sit back and wonder what would George Washington think of the space shuttle or SpaceX or the space station or some of these advance technologies."
Professor Rodi says driverless cars and drones will improve and we'll see more applications of artificial intelligence in lots of areas, like financial markets and outer space.
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Artificial intelligence will only improve over the next decade - KFI AM 640
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Accountability is the key to ethical artificial intelligence, experts say – ComputerWeekly.com
Artificial intelligence (AI) needs to be more accountable but ethical considerations are not keeping pace with the technologys rate of deployment, says a panel of experts.
This is partly due to the black box nature of AI, whereby its almost impossible to determine how or why an AI makes the decisions it does, as well as the complexities of creating an unbiased AI.
However, according to panelists at the Bristol Technology Showcase, transparency is not enough, with greater accountability being the key to solving many of the ethical issues surrounding AI.
Meaningful transparency doesnt simply follow from doing things like open sourcing the code, thats not sufficient, says Eamonn ONeill, professor of computer science at the University of Bath and director of the UKRI Centre for Doctoral Training in Accountable, Responsible and Transparent AI.
Code and deep learning networks can be opaque however hard you try to open them to inspection. How does seeing a million lines of code help you understand what your smartphones mid-ware is doing? Probably not a lot.
ONeill says that AI needs to be accompanied by a chain of accountability that holds the systems human operator responsible for the decisions of the algorithm.
We dont go to a company and say I cant tell if youve cooked the books because I cant access the neurons of your accountants nobody cares about accountants neurons, and we shouldnt care about the internal workings of AI neural networks either, he said.
Instead, ONeill says we should be focusing on outcomes.
John Buyers, chair of the AI and Ethics panel and a partner at law firm Osborne Clark, points to the example of Mount Sanai Hospital using an AI system called Deep Patient, which was made to trawl through thousands of electronic health records.
Over the course of doing that, Deep Patient became very adept at diagnosing, among other things, adult schizophrenia, which human doctors simply couldnt do, he says. They dont know how the system got to that, but it was of demonstrable public benefit.
Zara Nanu, CEO of human resources technology company Gapsquare, says: When we talk about bias, its bias in terms of the existing data we have that machines are looking at, but also the bias in algorithms we then apply to the data.
She gives the example of Amazon, which gathered a team of data scientists to develop an algorithm that would help it identify top engineers from around the world, who could then be recruited by the company.
All was going well except the machines had learnt to exclude women from the candidate pool, so it was down-scoring people who had woman on their CV, and it was actually scoring higher people who had words like lead or manage, she says.
Amazon came under scrutiny and tried to look how they could make it fairer, but they had to scrap the programme because they couldnt hand-on-heart say the algorithm wouldnt end up discriminating against another group.
Therefore, while accountability does not remove potential bias in the first place, it did make Amazon, as the entity operating the AI system, responsible for the negative effects or consequences of that bias.
However, Chris Ford, a Smith and Williamson partner responsible for a $270m AI investment fund, says theres a critical deficit in the way many corporate entities are approaching the deployment of the technology.
MIT Sloan and Boston Consultancy Group produced an interesting paper earlier this year surveying 3,000 companies globally, most of them outside North America, he says.
What was eye catching was that of those who responded, about half of them said they can see no strategic risk in the deployment of AI platforms within their business, and I find that quite extraordinary.
Ford says this is partly due to a fear of missing out on the latest technological trends, but also because there is not enough emphasis on ethics in education related to AI.
He notes the example of Stuart Russells book,Artificial intelligence: A modern approach, which has been through numerous iterations and is one of the most popular course texts in the world.
That textbook in its most recent form is up to 1,100 pages, he says. Its extraordinarily comprehensive, but the section that deals with ethics is covered in the first 36 pages.
So theres an issue on emphasis here, both in respect to the academic training of data scientists but also what theyre expected to engage with in the commercial world when they leave education.
In terms of bias, the panelists also note that what is socially normal or acceptable is biased in itself.
The question then becomes whose societal norms are we talking about? We are already seeing significant differences and perspectives in the adoption of AI in different parts of the world, says Ford.
Buyers summarised that a lack of bias is not the introduction of objectivity, but the application of subjectivity in accordance with societal norms, so its incredibly difficult.
The overall argument is that AI, like humans, will always be biased to a point of view, meaning transparency will only go so far in solving the ethical issues around the deployment of AI.
Using AI in contrast to humans can facilitate transparency we can fully document the software engineering process, the data, the training, the system performance these measures can be used to support systematic inspection, and therefore transparency and regulation, but accountability and responsibility must stay with the humans, says ONeill.
The Bristol Technology Showcase was held in November 2019, and focused on the impact of emerging technologies on both businesses and wider society.
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Accountability is the key to ethical artificial intelligence, experts say - ComputerWeekly.com
Schlumberger inks deal to expand artificial intelligence in the oil field – Chron
Oilfield service giant Schlumberger has inked a deal to expand its offerings of artificial intelligence products and services.
Oilfield service giant Schlumberger has inked a deal to expand its offerings of artificial intelligence products and services.
Oilfield service giant Schlumberger has inked a deal to expand its offerings of artificial intelligence products and services.
Oilfield service giant Schlumberger has inked a deal to expand its offerings of artificial intelligence products and services.
Schlumberger inks deal to expand artificial intelligence in the oil field
Oilfield service giant Schlumberger has inked a deal to expand the use of artificial intelligence technology in the oil patch.
In a statement, Schlumberger announced it had entered into an agreement the New York software company Dataiku.
Under the agreement, the two companies will work together to develop artificial intelligence products and services for Schlumberger's exploration and production customers.
Service Sector: Baker Hughes enters deal to boost AI in the oil field
With U.S. crude oil prices stuck in the mid-$50 per barrel range, many energy companies are adopting digital tools to increase efficiency and lower costs.
The deal between Schlumberger and Dataiku comes less than a month after oilfield service company rival Baker Hughes entered into a similar deal withtech giant Microsoft and Silicon Valley artificial intelligence company C3.ai.
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Headquartered in Paris with its principal offices in Houston, Schlumberger is the largest oilfield service company in the world with more than 100,000 employees in 85 nations.
The company posted a $2.2 billion profit on $32.8 billion of revenue in 2018.
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Schlumberger inks deal to expand artificial intelligence in the oil field - Chron
Boschs A.I.-powered tech could prevent accidents by staring at you – Digital Trends
Most cars sold new in 2019 are equipped with technology that lets them scope out the road ahead. They can brake when a pedestrian crosses the road in front of them, for example, or accelerate on their own when a semi passing a slower vehicle moves back into the right lane. Now, Bosch is developing artificial intelligence-powered technology that opens new horizons by teaching cars how to see what and who is riding in them. It sounds creepy, but it could save your life.
Boschs system primarily relies on a small camera integrated into the steering wheel. Facial-recognition technology tells it whether the driver is falling asleep, looking down at a funny video on a phone, yelling at the rear passengers, or otherwise distracted. Artificial intelligence teaches it how to recognize many different situations. The system then takes the most appropriate action. It tries to wake you up if youre dozing off, and it reminds you to look ahead if your eyes are elsewhere. Alternatively, it can recommend a break from driving and, in extreme cases, slow down the car to prevent a collision.
Driver awareness monitoring systems are already on the market in 2019. Cadillacs Super Cruise technology notably relies on one to tell whether the driver is paying attention, but Boschs solution is different because its being trained to recognize a wide variety of scenarios via image-processing algorithms. This approach is similar to how the German firm teaches autonomous cars to interpret objects around them. Real-world footage of drivers falling asleep (hopefully on test tracks, and not on I-80) shows the software precisely what happens before the driver calls it a night.
This technology can also keep an eye on your passengers. Thanks to a camera embedded in the rearview mirror, the system can keep an eye on the people riding in the back, and warn the driver if one isnt wearing a seat belt. It can even detect the position a given passenger is sitting in, and adjust the airbags and seat belt parameters accordingly. Safety systems are designed to work when someone is sitting facing forward and upright, but thats not always the case. If youre slouching in the back seat (admit it, it happens), the last thing you want is the side airbag to become a throat airbag.
Smartphone connectivity plays a role here, too. The same mirror-mounted camera recognizes when a child is left in the back seat, and it automatically sends an alert to the drivers smartphone. It notifies the relevant emergency services if the driver doesnt come back after a predetermined amount of time.
Looking further ahead, when autonomous technology finally merges into the mainstream, this tech could tell the car if the driver is ready to take over. Theres no sense in asking someone to drive if theyre asleep, or if theyve hopped over the drivers seat to chill on the rear bench. Autonomy will come in increments, so its not too far-fetched to imagine a car capable of driving itself at freeway speeds, when the lane markings are clear, but not in crowded urban centers.
The footage captured by the cameras cant be used against you or yours, according to Bosch, because its neither saved nor shared with third parties. Still, its a feature that will certainly raise more than a few concerns about privacy.
The technology could reach production in 2022, when European Union officials will make driver-monitoring technology mandatory in all new cars. Lawmakers hope the feature will save 25,000 lives and prevent at least 140,000 severe injuries by 2038. Theres no word yet on when (or whether) it will come to the United States. Bosch doesnt make cars it never has so its up to automakers to decide whether its worth putting in their new models.
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Boschs A.I.-powered tech could prevent accidents by staring at you - Digital Trends
Beethovens unfinished tenth symphony to be completed by artificial intelligence – Classic FM
16 December 2019, 16:31
Beethovens unfinished symphony is set to be completed by artificial intelligence, in the run-up to celebrations around the 250th anniversary of the composers birth.
A computer is set to complete Beethovens unfinished tenth symphony, in the most ambitious project of its kind.
Artificial intelligence has recently been used to complete Schuberts Unfinished Symphony No. 8, as well as to attempt to match the playing of revered 20th-century pianist, Glenn Gould.
Beethoven famously wrote nine symphonies (you can read more here about the Curse of the Ninth). But alongside his Symphony No. 9, which contains the Ode to Joy, there is evidence that he began writing a tenth.
Unfortunately, when the German composer died in 1827, he left only drafts and notes of the composition.
Read more: What is the Curse of the Ninth and does it really exist? >
A team of musicologists and programmers have been training the artificial intelligence, by playing snippets of Beethovens unfinished Symphony No. 10, as well as sections from other works like his Eroica Symphony. The AI is then left to improvise the rest.
Matthias Roeder, project leader and director of the Herbert von Karajan institute, told Frankfurter Allgemeine Sonntagszeitung: No machine has been able to do this for so long. This is unique.
The quality of genius cannot be fully replicated, still less if youre dealing with Beethovens late period, said Christine Siegert, head of the Beethoven Archive in Bonn and one of those managing the project.
I think the projects goal should be to integrate Beethovens existing musical fragments into a coherent musical flow, she told the German broadcaster Deutshe Welle. Thats difficult enough, and if this project can manage that, it will be an incredible accomplishment.
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It remains to be seen and heard whether the new completed composition will sound anything like Beethovens own compositions. But Mr Roeder has said the algorithm is making positive progress.
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The algorithm is unpredictable, it surprises us every day. It is like a small child who is exploring the world of Beethoven.
But it keeps going and, at some point, the system really surprises you. And that happened the first time a few weeks ago. Were pleased that its making such big strides.
There will also, reliable sources have confirmed, be some human involvement in the project. Although the computer will write the music, a living composer will orchestrate it for playing.
The results of the experiment will be premiered by a full symphony orchestra, in a public performance in Bonn Beethovens birthplace in Germany on 28 April 2020.
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Beethovens unfinished tenth symphony to be completed by artificial intelligence - Classic FM