Artificial intelligence (AI) is making all the difference between innovators and laggards in the global marketplace. Yet, implementing a state-of-the-art DataOps operation involves a long-term commitment to putting in place the right people, processes and tools that will deliver results.
In this post, we look at three organizations that are doing cutting-edge work in the field of DataOps. We look at the specific strategies they use and the results they’ve seen as they navigate the uncharted waters of DataOps. Read More
Monthly Archives: July 2019
How the new 'Lion King' came to life
When I was told that I’d be visiting the production of Disney’s new “Lion King,” I had a hazy idea of what to expect — sets recreating the iconic landscapes of the animated film, maybe some actors in costumes or motion capture suits.
Instead, if you’ve seen the movie (which came out on July 19), you probably won’t be surprised to hear that there wasn’t a single set or costume in sight. After all, even though the film looks like a live action remake of “The Lion King,” every shot except for the first was created on a computer. Read More
Amazon launches Neural Text-To-Speech and newscaster style on AWS Polly
Not to be outdone by Google’s WaveNet, which mimics things like stress and intonation in speech by identifying tonal patterns, Amazon today announced the general availability of Neural Text-To-Speech and newscaster style in Amazon Polly, its cloud service that converts text into speech.
As Amazon Web Services tech evangelist Julien Simon noted in a blog post, Neural Text-To-Speech delivers significant improvements in speech quality by increasing naturalness and expressiveness. Read More
Neural Decipherment via Minimum-Cost Flow: from Ugaritic to Linear B
In this paper we propose a novel neural approach for automatic decipherment of lost languages. To compensate for the lack of strong supervision signal, our model design is informed by patterns in language change documented in historical linguistics. The model utilizes an expressive sequence-to-sequence model to capture character-level correspondences between cognates. To effectively train the model in an unsupervised manner, we innovate the training procedure by formalizing it as a minimum-cost flow problem. When applied to the decipherment of Ugaritic, we achieve a 5.5% absolute improvement over state-of-the-art results. We also report the first automatic results in deciphering Linear B, a syllabic language related to ancient Greek, where our model correctly translates 67.3% of cognates. Read More
MobilBye: Attacking ADAS with Camera Spoofing
Advanced driver assistance systems (ADASs) were devel-oped to reduce the number of car accidents by issuing driveralert or controlling the vehicle. In this paper, we tested therobustness of Mobileye, a popular external ADAS. We injectedspoofed traffic signs into Mobileye to assess the influence ofenvironmental changes (e.g., changes in color, shape, projectionspeed, diameter and ambient light) on the outcome of an attack.To conduct this experiment in a realistic scenario, we used adrone to carry a portable projector which projected the spoofedtraffic sign on a driving car. Our experiments show that it ispossible to fool Mobileye so that it interprets the drone carriedspoofed traffic sign as a real traffic sign. Read More
Artificial Intelligence, Cyberattacks and Nuclear Weapons: A Dangerous Combination
Artificial intelligence (AI) — defined by John McCarthy, one of the doyens of AI, as “the science and engineering of making intelligent machines” — is slowly gaining relevance in the military domain. While commercial use of AI is widening, there are only three countries that are reported to be developing serious military AI technologies: the United States, China and Russia. AI promises a significant military advantage to a nation’s offensive and defensive military capabilities.
AI now has the capacity to be merged with sophisticated but untried, new weaponry, such as offensive cyber capabilities. This is an alarming development, as it has the potential to destabilize the balance of military power among the leading industrial nations. Read More
The Top-10 Russian Artificial Intelligence Startups
As China and the US are fighting for AI supremacy and the EU is scrambling to catch up, Russia’s growing its footprint in AI with a seemingly low-key approach. Hearing less about Russian AI companies doesn’t mean they don’t exist though. The Russian government’s investments into AI have been dwarfed by the billions of dollars China and the US have been spending but this may change with a growing number of public-private partnerships and the involvement of the Russian Ministry of Defense in AI projects. Russia also has a strong venture capital infrastructure in place that has helped grow her “AI industry” up to this point. Read More
State of AI: Artificial Intelligence, the Military and Increasingly Autonomous Weapons
As artificial intelligence works its way into industries like healthcare and finance, governments around the world are increasingly investing in another of its applications: autonomous weapons systems. Many are already developing programs and technologies that they hope will give them an edge over their adversaries, creating mounting pressure for others to follow suite.
These investments appear to mark the early stages of an AI arms race. Much like the nuclear arms race of the 20th century, this type of military escalation poses a threat to all humanity and is ultimately unwinnable. It incentivizes speed over safety and ethics in the development of new technologies, and as these technologies proliferate it offers no long-term advantage to any one player. Read More
Weapons of the weak: Russia and AI-driven asymmetric warfare
Speaking to Russian students on the first day of the school year in September 2017, Putin squarely positioned Russia in the technological arms race for artificial intelligence (AI). Putin’s comment (see above) signaled that, like China and the United States, Russia sees itself engaged in direct geopolitical competition with the world’s great powers, and AI is the currency that Russia is betting on. But, unlike the United States and China, Russia lags behind in research and development on AI and other emerging technologies. Russia’s economy makes up less than 2 percent of global GDP compared to 24 percent for the United States and 15 percent for China, which puts Russia on par with a country like Spain.[3] Despite Putin’s focus on AI, the Russian government has not released a strategy, like China has, on how the country plans to lead in this area. The Russian government’s future investment in AI research is unknown, but reports estimate that it spends approximately $12.5 million a year[4] on AI research, putting it far behind China’s plan to invest $150 billion through 2030. The U.S. Department of Defense alone spends $7.4 billion annually on unclassified research and development on AI and related fields. Read More
Putin outlines Russia’s national AI strategy priorities
Russian President Vladimir Putin has offered the best insight yet at what shape the country’s AI strategy will take.
Putin ordered his government apparatus on February 27th to formulate a national artificial intelligence strategy by June 25th. With that date quickly approaching, the world is waiting to see Russia’s AI plans.
Back in September 2017, Putin famously said the nation which leads in AI “will become the ruler of the world.” Understandably, Putin’s comments generated fear of a cold war-like rush to militarise AI technology.
The Russian leader’s most recent speech won’t help to ease those concerns after reiterating that AI offers unprecedented power, including military power, to any government that leads in the field. Read More
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