пятница, 23 февраля 2018 г.

The flowers that give us chocolate are ridiculously hard to pollinate

FLOWERS FOR CHOCOLATE  Pale petals curl over a cacao flower’s male parts. Here, two developing fruits, or seedpods (top left), will eventually ripen, housing the seeds that give the world chocolate.

A complicated reproductive system makes pollination a tough job


BY 

How to build a human brain

BRAIN-MAKING 101  As blobs of two types of brainlike tissue fuse, interneurons (green) migrate from the left clump to the right, linking with neurons (not stained) in the right blob. On both sides, neural support cells called glia appear in purple.


Some steps for growing mini versions of human organs are easier than others


BY 

воскресенье, 11 февраля 2018 г.

7 Big Problems with the Internet of Things


In a few short years, the Internet of Things (IoT) has gone from a technology — or set of technologies — that were cutting edge to the situation today where connected household items, or automobiles, are common. However, growth is only really gathering speed now with San Francisco-based Cisco estimating that the "Internet of Everything cisco article" — its take on the IoT — could have has many as 50 billion connected devices by 2020.
According to Helsinki, Finland-based F-Secure, a cybersecurity company citing research from Gartner, over the next two years, the number of IoT devices entering households will climb steeply from nine devices per household currently to 500 by 2022, with IoT connectivity being bundled into products whether people want it or not.
In fact according to Mikko Hypponen, chief research officer for F-Secure in research on the IoT published last month, in the future, devices without IoT capabilities may be more expensive because they'll lack data that can be harvested by manufacturers. It’s this very data that makes the IoT such an interesting proposition for enterprises. That data, though, comes with risks, along with a number of other notable risks and problems associated with the IoT that enterprises will have to overcome in the coming years.
Last month, the World Economic Forum published its Global Risks Report for 2018, the 13th year it has published it. Each year, researchers with the Global Risks Report work with experts and decision-makers across the world to identify and analyze the most pressing risks that the world face. As the pace of change accelerates, and as risk interconnections deepen, this year’s report highlights the growing strain we are placing on many of the global systems we rely upon. The IoT and the problems related to cyberattacks take a prominent position in the report.
If the IoT has a problem, or is exposed to weaknesses, then the enterprises that are connected to it are equally threatened. In fact, while security is undoubtedly one of the major issues impacting the development, there are a number of other problems that stem directly from this. Here are 7 major IoT problems for enterprises connecting to the IoT.

1. Walled Off Internet

According to the World Economic Forum, the growing number of cross border attacks will start pushing national governments towards breaking up the internet in national, or even regional “walled gardens.” There are other pressures too that will push them to do this, including economic protectionism, regulatory divergence and the loss of government power relative to global online companies.
This will create major problems for the concept — and practice of a global IoT — leading to the erection of barriers to the flow of content and transactions. “Some might welcome a move towards a less hyper-globalized online world, but many would not, resistance would be likely, as would the rapid growth of illegal workarounds. The pace of technological development would slow and its trajectory would change,” the report reads.

2. Cloud attacks

Given that a large amount of the data that will run the Io T will be stored in the cloud it is likely that cloud providers will be one of the principle targets in this kind of war. While there is growing awareness of this problem, cybersecurity is still under-resourced in comparison to the potential scale of the threat. To get some kind of idea of the problem, the World Economic Forum report cites analysis that suggests that the takedown of a single cloud provider could cause $50 billion to $120 billion of economic damage — a loss somewhere between Hurricane Sandy and Hurricane Katrina.
The annual economic cost of cybercrime is now estimated at north of $1 trillion, a multiple of 2017’s record-year aggregate cost of approximately $300 billion from natural disasters.

3. AI-Built Security Issues

Although the threat magnitude of ransomware has already grown 35x over the last year with ransomworms and other types of attacks, there is more to come. Rick Pither, who leads Austin, Texas-based SparkCognition’s Global Security website Sales and Embedded OEM business agrees that the problems for cloud vendors are only emerging.
He said that the next big target for ransomware is likely to be cloud service providers and other commercial services with a goal of creating revenue streams. The complex, hyperconnected networks cloud providers have ?developed can produce a single point of failure for hundreds of businesses, government entities, critical infrastructures, and healthcare organizations. If not in the next year, he said soon we will begin to see malware completely created by machines based on automated vulnerability detection and complex data analysis. Polymorphic malware is not new, but it is about to take on a new face by leveraging AI to create sophisticated new code that can learn to evade detection through machine written routines.

4. Botnet Problems

Millions of new connected consumer devices make a wide attack surface for hackers, who will continue to probe the connections between low-power, somewhat dumb devices and critical infrastructure, Shaun Cooley, VP and CTO at San Jose, California based Cisco website said. The biggest security challenge he sees is the creation of Distributed Destruction of Service (DDoS) attacks that employ swarms of poorly-protected consumer devices to attack public infrastructure through massively coordinated misuse of communication channels. 
IoT botnets can direct enormous swarms of connected sensors like thermostats or sprinkler controllers to cause damaging and unpredictable spikes in infrastructure use, leading to things like power surges, destructive water hammer attacks, or reduced availability of critical infrastructure on a city or state-wide level. Solutions for these attacks do exist, from smarter control software that can tell the difference between emergency and erroneous sensor data, and standards that put bounds on what data devices are allowed to send, or how often they're allowed to send it. But the challenge of securing consumer-grade sensors and devices remains, especially as they connect, in droves, to our shared infrastructure. 

5. Limited AI

AJ Abdallat is CEO of Beyond Limits website, an organization that was born from the labs of the Caltech deep space program. He points out that most of the current AI offerings on the market have substantial limits. After all, the machine learning and big data based AI that currently pervade are powerful tools for identifying associations in large quantities of data, but don’t have much on humans in terms of working out the complex phenomena of cause and effect, or to identify modifiable factors that can engender desired outcomes.
As big data and machine learning powered AI’s gains processing power, they can incorporate into their algorithms more and more information, more and more variables that may affect data associations. But with little human intervention, inevitably some variables may display strong correlation by pure chance, with little actual predictive effect. 
The practical applications of AI to the IoT include, Smart IoT that connects and optimizing devices, data and the IoT; AI-Enabled Cybersecurity that offers data security encryption and enhanced situational awareness to provide document, data, and network locking using smart distributed data secured by an AI key.

6. Lack of Confidence

Amsterdam, Netherlands-based Gemalto is a cybersecurity firm that has researched the impact of security on the development of the IoT. If found that that 90 percent of consumers lack confidence in the security of Internet of Things devices. This comes as more than two-thirds of consumers and almost 80% of organizations support governments getting involved in setting IoT security. In fact its recent State of IoT Security research report, released at the end of October showed the following data.
  • 96 percent of businesses and 90 percent of consumers believe there should be IoT security regulations
  • 54 percent of consumers own an average of four IoT devices, but only 14 percent believe that they are knowledgeable on IoT device security
  • 65 percent of consumers are concerned about a hacker controlling their IoT device, while 60 percent are concerned about data being leaked
"It's clear that both consumers and businesses have serious concerns around IoT security and little confidence that IoT service providers and device manufacturers will be able to protect IoT devices and more importantly the integrity of the data created, stored and transmitted by these devices," said Jason Hart, CTO of Data Protection at Gemalto said in a statement about the report. "Until there is confidence in IoT amongst businesses and consumers, it won't see mainstream adoption,” said Hart.

7. Understanding IoT

In 2018, the real issue is how to increase the ability for people to understand the changes and their implications more clearly, and to take concrete actions to take advantage of the potential upside. "The pace of change has exceeded the rate of human capability to absorb — the cup is already full," said Jeff Kavanaugh, VP and Senior Partner in High Tech & Manufacturing for Infosys website.
Internet of Things is moving into it’s adolescence as connected devices become smarter and more immersive, and expectations to convert IoT data to insights and financial value increase. Also, algorithms and data visualization templates have evolved so that new use cases can take advantage of earlier ones. The exponential adoption of IoT will drive down sensor and acquisition costs, enabling more and more viable business cases that have previously been too expensive. 


12 Emerging Internet of Things (IoT) Trends That Will Become Mainstream In 2018


In November, in a dive into what is driving enterprise interest in the Internet of Things (IoT) we found that, for the moment at least, enterprises are still wrestling with the problems the IoT poses rather than harvesting the benefits that it offers. There is nothing unusual in this given that the IoT is still a relatively new phenomena and there are considerable — and justified — security fears dominating enterprise strategies around the IoT.
But will security dominate IoT this year. And what about the Industrial IoT — will it move further away from the IoT as some have suggested or will they become closer? At the beginning of 2016 we saw that the really big tech vendors likes Microsoft were dedicating significant resources to building IoT incubators that would focus on enterprise, industry and smart cities. However, now, with security solutions getting "smarter" and enterprises actively looking to harvest consumer data harvested from the IoT, the connection between IoT and Industrial IoT is getting narrower and closer to Cisco’s idea of the Internet of Everything (IoE).
Mark Barrenechea, OpenText CEO and CTO shared that while we might not feel the immediate effects of the IoT, its potential impact is huge. Advances in IoT-connected biotechnology will take healthcare to the next level, with around-the-clock monitoring, targeted treatment, and even automated doses of medication. In smart cities, when everything is connected to the IoT grid, autonomous vehicles will eliminate car crashes caused by human error to save one million lives annually. “In the Intelligent Enterprise, the IoT will connect the global supply chain from end-to-end, enabling pervasive visibility, proactive replenishment, and predictive maintenance. With the IoT, data-driven decision making will become standard in all industries and in our daily lives,” he says. So what will happen with the IoT and the Industrial IoT, and what will enterprises be doing to optimize their investments?

1. Security

“The pace of change has exceeded the rate of human capability to absorb — the cup is already full. In 2018, the real issue is how to increase the ability for people to understand the changes and their implications more clearly, and to take concrete actions to take advantage of the potential upside,” says Erick Dean, Product Director of IoT, at San Francisco-based Splunk. As a result, he has security at the top of his list for IoT trends in 2018, but it’s not all that’s going to happen.
In 2018, security for IoT will be under heavy scrutiny. Cybersecurity risk will increase exponentially as people, processes and businesses continue to connect every part of people’s daily lives, as well as national economies. "We are looking into a future where attacks can be orchestrated not just from public networks, but from private devices such as a smartphones or a smart home,” he says. His other predictions for 2018 go as follows.

2. Major Adopters

Industrial asset management, fleet management in transportation, inventory management and government security will be the hottest areas for IoT growth in 2018. With increasing connectivity between people, data and things, the public sector will begin embracing smart cities, where sensors and automation enhance the reliability of services, especially in the areas of safety and environment. IoT sensor data enables use cases including improved air quality, optimized traffic patterns, reduced safety incidents, traffic fire incident prediction, and improved citizen identity.

3. Digital Transformation

Digital transformation initiatives — especially those centered around customer experience — will drive IoT expansion velocity. Building a technology infrastructure is relatively easy. The challenge is operationalizing data-driven decision-making that impacts the health of the business.

4. Machine Learning

Machine learning and AI represent a tremendous opportunity to IoT. Being able to predict when machinery will need to be repaired, self-optimizing production, and demand response are only a few application examples. With existing network infrastructure likely to be used for "connected things" the investment spend on analytics will be higher as companies find new ways to make sense of the vast amounts of smart device-generated data.

5. IoT Growing Up

Jeff Kavanaugh, VP and Senior Partner in India-based Infosys, told us that while problems persist, the IoT is starting to mature and that enterprises will start trying to monetize the data that is harvested from the IoT. Those that are using the IoT will also start to realize that IoT is difficult "to do."
According to Kavanaugh, connected devices will become smarter and more immersive, and expectations will increase to convert IoT data to insights and financial value. Algorithms and data visualization templates have now evolved so that new use cases can take advantage of earlier ones. The exponential adoption of IoT will drive down sensor and acquisition costs, enabling more and more viable business cases that have previously been too expensive.

6. Executive Expectations

He added that just as enterprise resource planning maturity raised expectations about foundational data consistency, robotic process automation will raise executive expectations about performance levels for repetitive processes. Companies will get better at scaling automation, moving from interesting proofs of concept to systemic enterprise processes that generate efficiency at scale.
Fast-moving technologies will influence colleges and universities to adopt greater computer programming and data analysis courses. However, universities must complement these with a focus on critical thinking and empathetic skills to meet the growing need of enduring skills in the digital world.

7. Revenue Model Challenges

Los Angeles-based Inspire is a company that simplifies consumer adoption of clean energy and smart home technologies. Patrick Maloney, CEO and of the company points out that despite the euphoria around the IoT, there are no guarantees that companies that make a business out of it are going to make money. There has been no shortage of innovation and new product offerings for the smart home this past year, driven largely by advancements in AI, automation, and voice-enabled technology. This is unlikely to change any time soon. However, he said, going to market is hard, retail shelves are crowded, and products aren’t highly differentiated making it difficult to maintain long-term growth. The revenue models for most smart home products and devices are transactional, one-time purchases.
Unless you are Amazon or Google, creating predictable and capital-efficient revenue streams is not likely. Companies that will succeed in the smart home space are those that can make the transition to a recurring revenue business model, and also create more value and efficiency for the consumer. “Smart homes shouldn’t just be smart for the sake of being smart, but instead improve consumers’ everyday lives. By focusing on smart home services, not just the hardware, we’ll see companies achieve both,” he says.

8. Blockchain

Mike Bell, EVP IoT & Devices at London, UK-based Canonical points to the rise of blockchain in IoT as one of the major emerging trends for 2017 and says that this and machine learning will become established elements of the IoT landscape over the course of the next 12 months. “Two of the most interesting IoT developments to emerge in 2017, with the most potential for innovation, were blockchain and machine learning. They likely won't go straight to market in the new year — we'll likely see more proofs of concept (PoC) instead — but, we have seen some fascinating PoCs already,” he said.
Machine learning has also yielded some interesting case studies to date. While it won't move entirely to edge there are some compelling examples so far, like retail shop security cameras with streaming video, where machine learning can be utilized to identify patterns of potential theft, perform facial without digging into customers' personal data, to head off security and privacy concerns.

9. Analytics Literacy

Alluvium is a New York City start-up that uses machine learning and artificial intelligence to turn massive streams of complex industrial data into simple insights enabling factories to reach operational stability. Its founder and CEO, Dean Conway, says that on the industrial IoT, organizations will move from making investments in digital infrastructure to making investments in digital literacy.
Conway predicts that the curve of investment in the industrial IoT will begin to bend toward analytics capabilities. This will likely manifest as a blend of hiring for new roles, such as data scientists and data engineers; a move to multi-cloud to investigate capabilities across incumbent cloud providers, such as Microsoft, Amazon, and Google; and, experimentation in investment with cutting edge analytics tools.

10. Mergers And Acquisitions

There will also be increased merger and acquisition activity for advanced IoT capabilities among large OEMs. This dovetails with the large appetite from industrial OEMs to bring advanced digital and analytics capabilities in-house as a means of accelerating their competitive advantage. Because software engineering and data science are not core competencies of OEMs, it will continue to be more efficient for these organizations to bring these capabilities into their stacks. As digital transparency continues to increase at every level of production the competition among OEMs at the software and services layer will emerge as the deciding differentiator in 2018.

11. Convergence And Employment

Joseph Bradley agrees that blockchain and deeper mining of data will be major trends in 2018, but also believes that the IoT will start driving changes in the jobs market.
As is Global Vice President for Digital and IoT Advanced Services at San Jose, Calif.-based Cisco he points out that the integration of social, business and political will force companies to enter what was previously known as a “no fly zone.” 3As competition for technology talent intensifies, silence won’t be an option for businesses. Millennials and generation Z — both of which will dominate the U.S. workforce by 2020 — will reshape the employment landscape due to their convictions and the expectation that employers demonstrate similar convictions,” he says.
To maintain a workforce and drive success, companies must to listen to their employee base and apply corporate principles to social and political activities. In 2018 and beyond, “taking a stand” will become the norm as companies hire upcoming generations who thrive on a values-driven corporate culture.

12. Next Generation Manufacturing

Chris Steck also works for Cisco as Head of Standardization, IoT & Industries. He says the IoT boom will facilitate the emergence of next generation manufacturing.  Manufacturing is buzzing about Industry 4.0, according to Steck,  the term for a collection of new capabilities for smart factories, that is driving what is literally the next industrial revolution. “IoT technologies are connecting new devices, sensors, machines, and other assets together, while Lean Six Sigma and continuous improvement methodologies are harvesting value from new IoT data. Early adopters are already seeing big reductions in equipment downtime (from 15 to 95%), process waste and energy consumption in factories. 
There are more than 50 billion connected devices in circulation today, generating an excess of eight zetabytes of data between them. And that number is only likely to expand. However, only one percent of Internet of Things (IoT) data is currently analyzed and utilized. But all this is changing. Soon, IoT deployments will include a holistic mobile and cloud platform, consisting of planning and analysis with digital twins, operational autonomy and augmented human and machine interactions using cognitive AI services, predictive analytics, and supporting applications.  This may be for the medium term but the early stages of this change will be seen over the course of 2018.