Eva Chen Trend Micro
Eva Chen, Trend Micro
Time is running at a crazy speed in the field of technology. When Trend Micro has founded nearly 30 years ago, mobile phones were relatively difficult to use, disproportionately expensive and had a rather limited “intelligence”. They are now more powerful than the NASA devices that allowed humans to walk on the moon! Over the years, the mobility industry has experienced remarkable growth, as evidenced by the success of the Mobile World Congress (MWC) in Barcelona.
The mobile has indeed become the epicenter of the connected world. More than ever, smartphones – and connected objects (IoT) – impact every aspect of our daily lives. But in this increasingly connected digital world, new risks are emerging. Only connected intelligence can help build a safer connected world.
A world dominated by data
Connected objects surround us. They govern our hobbies, make us more productive at work, happier and healthier. They contribute to the smooth running of our factories, streamline work processes and optimize the various services provided.
The Gartner estimates that 20.4 million objects connected to the planet by 2020. But these generate an astronomical amount of data.
Risks are everywhere
The connected world in which we live is, however, increasingly exposed to cyber threats. We see it in many areas:
– The smart home: The Mirai botnet has compromised mass connected devices to launch DDoS attacks that have had a major impact on the Internet in 2016. Everything related to the home, from baby phones to connected locks, can be impacted.
– Smart factories: Hackers have also targeted connected objects within factories and critical infrastructures. The latest example is the attack of a Ukrainian energy supplier whose hundreds of thousands of users suffered a breakdown in December 2015 and 2016. A Trend Micro study just revealed how the cities of ‘Are particularly vulnerable to potential attacks.
– Connected cars: Researchers have also repeatedly shown that unprotected connected vehicles can be hacked, with far-reaching consequences, with hackers being able to take remote control of the steering wheel, brakes or engine.
The recipe for success
It is becoming increasingly difficult to protect the growing number of connected devices. Buggy codes, open network ports, bad authentication, undetected files, usage changes, insecure network protocols … all this represents an additional challenge. Fortunately, there is a solution. The recipe for success is based on three points: anticipate the evolution of infrastructures towards the Cloud, connected objects, and 5G; integrate the change in user behavior, and protect against all threats.
It will not be easy. The two historically separate worlds of IT and OT are rapidly converging into the IoT sphere, exposing companies and their employees to new risks – while the industry faces a shortage of cybersecurity skills. Success, however, will depend on the choice of security based on intelligence connected to all levels of IoT: hardware (home appliance, industrial machine, connected car); the network; the control center (voice assistance, ICS, Cloud controller); and the “data analyzer” in the cloud.
In practice, this means: guard against machine vulnerabilities; be vigilant about the network inspection; strengthen systems at the control center level and protect servers in the cloud. More importantly, this approach must be accompanied by connected intelligence that collects data from millions of IoT sensors around the world, analyzing them in the cloud, then blacklisting and blocking connections from suspicious devices. Artificial intelligence also has an important role to play here: finding the needle in the haystack, ie suspicious scenarios that may herald future attacks within IoT data.
In order to stay ahead of the hackers, it is therefore essential to ensure data security and the proper functioning of key systems by relying on the power of connected intelligence and strong partnerships between major players. Of the industry.
Eva Chen is CEO and co-founder of Trend Micro
Tesla Self-Driving Chip
To build its own self-driving chips Tesla was announced after their second-quarter income report that Tesla is processing the creation of their own computer chips where Elon Musk revealed last December, this isn’t something new but,
Musk says that the new silicon is faster than the old products that were made by NVIDIA, in which he explained that the old ones are only able to deal with 200 frames per second from the cameras around the car, unlike the new Tesla Chip where will be able to handle about 2,000 frames per second…
Tesla Motors Inc. Tests Self-Driving Technology
This isn’t going to make a big impact on NVIDIA, they say the sales where small and it’s not going to have a material impact.
Tesla says there will be some safety improvements to in Autopilot will come soon, with software V9.0. it will be the beginning of what the company calls it “on-ramp to off-ramp” driving, where the car handles lane changes on the freeway automatically.
What are the top 6 Self Driving Car Race
Do you know the hottest trend all big companies pursuing right now? It is self driving car technology, the technology that allows car drive itself. All big companies, automakers, tech, software makers, want to take part in it, starting from Google, Apple, General Motor, Uber, Ford, Volkswagen, Tesla, Baidu, Samsung, Nvidia, Intel, to name a few, don’t forget startups like Zoox, autonomy, Aurora Innovation, and Drive.ai as well. What are the top 6 Self Driving Car Race ?
Here is the current state of several companies pursuing self-driving car technology.
1. Waymo (Google)
Google is a pioneer for a self-driving car, starting back then in 2010. At first, it was just moonshot from X, subsidiary of Google founded by Sebastian Thrun, and supervised by Chris Urmson and Anthony Levandowski. Then, because of machine learning development, a self-driving car that seemed far-fetched is now almost ready. In 2016, Google spins off its self-driving car arm into a stand-alone company called Waymo.
The analyst believes Waymo is far ahead than its competitors when it comes to the self-driving car. It has expertise in developing self-driving car software, it has logged more than 5 million self-driven miles on the road. It has a partnership with automakers like Fiat Chrysler, Jaguar, and soon Honda. It is also testing self driving car service without a human test driver in Phoenix.
The biggest American automaker bought silicon valley startup Cruise Automation in 2016 for $1 billion to catch up with a self-driving car race. GM CEO Mary Barra believes that Cruise team, led by Kyle Vogt and Daniel Kan, will help GM to make self driving car reality. Currently, GM and Cruise are testing more than 100 Chevy Bolt self-driving car in San Francisco. This week, Cruise gets $2.25 billion investment from Softbank Vision Fund that will help them accelerate effort for deploying self-driving car as soon as possible.
Tesla, led by Elon Musk, is producing Model S, Model X, and Model 3 with Autopilot technology. The difference they have is Tesla cars don’t use Lidar that most automaker use for its self-driving car technology. This autopilot currently becomes a controversy as there is fatality accident in March.
Ride-sharing juggernaut also develops self-driving car technology, citing the previous ambitious goal of founder Travis Kalanick. Uber lately faces unfortunate event as its car killed a pedestrian in Arizona.
5. Aurora Innovation
It’s startup founded by Chris Urmson, Sterling Anderson, and Drew Bagnell. These 3 are veteran in self driving car technology. Chris Urmson previously led the team in Google X, Sterling Anderson previously led Tesla Autopilot project, and Drew Bagnell was founding member of Uber Advanced Technology Center. They are currently developing self-driving car software and engage in a relationship with Volkswagen and Hyundai.
It’s startup founded by Ph.D. students of Stanford. AI expert Andrew Ng also become its board. The main difference between drive.ai and others are it develops a car that can interact with its environment such as pedestrian through its board above the car. Drive.ai recently announced that it will launch a ride-hailing service using autonomous vehicles in Frisco, Texas, in July.
Oracle extends the Autonomous Cloud Platform Services
With built-in innovative artificial intelligence (AI) and machine learning algorithms, these revolutionary new PaaS providers automate and remove key jobs to allow organizations to reduce cost, reduce risk, accelerate innovation, and also receive predictive insights. Before this year, Oracle Cloud made accessible the world’s earliest Autonomous Database for information warehouse workloads.
The business is dedicated to incorporating self-driving, self-securing, and self-repairing capabilities to all its own PaaS services coupled with specific autonomous capacities for every operational area.
Besides the current news, Oracle intends to launch more autonomous solutions later in the calendar year 2018 centered on cellular and chatbots, information integration, Blockchain, management and security, and extra database workloads, such as OLTP.
“Embedding AI and machine learning from such cloud solutions can assist organizations to innovate in revolutionary new ways,” said Amit Zavery, executive vice president of growth, Cloud Platform.
“These cloud solutions are the most up-to-date in a succession of measures from Oracle to integrate industry-first autonomous capacities that will enable clients to significantly lower operational expenses, improve productivity, and reduce risk.”
As companies focus on delivering creation quickly, they need a safe set of detailed, integrated cloud solutions to construct new programs and operate their most demanding enterprise workloads.
Just Oracle’s cloud providers may automate key operational purposes such as tuning, patching, upgrades, and backups while working on delivering optimum performance, higher availability, and secure IT systems.
Recently accessible autonomous solutions comprise Oracle Autonomous Analytics Cloud, Oracle Autonomous Integration Cloud, and Oracle Autonomous Visual Builder Cloud. These solutions help organizations easily assemble and deploy contemporary applications, in addition to incorporate and examine critical organizational information.
Oracle Autonomous Analytics Cloud combines machine learning, flexible intellect, and support automation to make an analytics platform which breaks down barriers between people, areas, information, and systems, basically altering the way people analyze, comprehend, and act on information.
- Empowers business users to discover more insights, fast. Users may ask questions in their mobile devices, and natural language processing transforms these queries to queries in the backend to deliver rich visualizations in their apparatus. It uses machine learning how to obtain intelligence and proactively indicate insight on information the user may not have requested for.
- Shows hidden routines and performance drivers via predictive automatic and insights natural-language explanations powered by machine learning.
- Offers predictive analytics on IoT data using domain-specific machine learning algorithms on large quantities of detector data and historic patterns of collapse.
Oracle Autonomous Integration Cloud accelerates electronic transformation by allowing business processes spanning multiple Oracle and non-Oracle SaaS and on-premises software via a combination of machine learning, embedded best-practice advice, and pre-built software integration and process automation.
- Speeds up integrations from the intricate process of mapping features of items across two different programs utilizing audience sourced information of executed integrations, and machine learning how to deliver visual recommendations on the way to connect those items.
- Delivers bright dynamic flexible case management by offering APIs to embed AI/machine learning frameworks, and indicate the following best action within an automated process stream.
- Increases resiliency and performance by supplying self-driven and tuning Integrations to handle massive workloads intelligently.
- Enables Robotic Procedure Automation together with AI/machine learning how to automate the past portion of case management or process automation using programs which aren’t API enabled.
Oracle Autonomous Visual Builder Cloud helps accelerate cellular and internet application development and deployment by allowing business users and programmers to create these programs with no coding. Learn more here.
- Automates code creation utilizing the hottest mobile technologies with only click installation allowing rapid application development even by line-of-business users.
- Automates delivery of mobile applications across multiple platforms such as iOS and Android.
Easily scalable and based on conventional open-source tech (Oracle JET, Swagger)
Oracle Cloud Platform services all discuss foundational autonomous capacities including:
- Self-Driving to Lower Costs and Increase Productivity: Remove human labor to supply, secure, track, copy, recover and purge. Carefully update and patch itself while operating.
- Instantly increase and shrink computer or storage without any downtime.
- Self-Securing to Reduce Risk: Shield from outside attacks and malicious internal customers. Automatically use security updates while working to safeguard against cyber attacks, and encrypt all information.
- Self-Repairing for Greater Entry: Provide automatic protection against most planned and unplanned downtime with up to 99.995 percent accessibility, leading to less than 2.5 minutes of downtime each month including planned maintenance.
Organizations can attempt Oracle Autonomous Cloud Platform solutions, such as Oracle Autonomous Data Warehouse Cloud by simply signing up for a Free Oracle Cloud Trial through http://cloud.oracle.com/tryit
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