Apple Offers iPhone Users Apology, $29 Battery Replacement Deal

Today’s topics include Apple's apology and offer of a replacement deal for tired iPhone batteries; security flaws found in Sonos and Bose internet-connected speakers; IBM's progress in developing the quantum computing technology in its Q Systems; and the new Kubernetes auto-scaling system that Microsoft developed with partner Litbit to right-size machine learning cloud workloads.

In a Dec. 28 letter Apple has apologized for battery life issues that have affected the performance of its iPhones and offered customers a $29 battery replacement deal.

In the letter, Apple stated "we have never—and would never—do anything to intentionally shorten the life of any Apple product, or degrade the user experience to drive customer upgrades.”

The apology and the supporting documentation attempts to regain credibility that was lost after mobile technology researchers revealed that Apple used iOS updates to throttle the performance of older iPhone models to adjust for the reduced charging capacity of their aging batteries. The performance adjustment was done without owners' knowledge or acceptance. The replacement deal allows owners of the iPhone 6 and later to replace the batteries in their phones at a $50 discount.

Trend Micro on Dec. 27 published a 47-page report titled "The Sound of a Targeted Attack," which documents multiple flaws in connected home speakers from Sonos and Bose and provides insight into how attackers can use the vulnerabilities to exploit users. The impacted systems include the Sonos Play:1, Sonos One and Bose SoundTouch systems.

Sonos has already responded to Trend Micro about the findings and has issued an update for its users. Trend Micro also reached out to Bose, but has not yet received a response.

The Sonos flaws could have enabled an attacker to access user information and potentially gain limited control of a device to play songs. Trend Micro also found that there was an unauthenticated status site page being served by Sonos devices. The unfortunate truth of IoT connected devices is that they can represent a potential unauthorized entry point into a network if not properly secured.

Throughout 2017, IBM has made major investments in quantum computing. In March, they rolled out IBM Q, a quantum computing environment accessible via the IBM Cloud platform and an API that enables Quantum Experience users to run sophisticated experiments in the cloud-based quantum environment.

In November, IBM announced that the first Q systems available online will have a 20-qubit processor and that engineers will upgrade the systems throughout 2018. They also created an operational prototype 50-qubit processor, which will run in the next generation of IBM Q systems. Earlier this month, IBM unveiled the first dozen businesses, including prominent financial services and auto-maker companies that will have early access to the IBM Q quantum computing system.

Dario Gil, vice president of AI and IBM Q, said “We are currently in a period of history when we can prepare for a future where quantum computers offer a clear computational advantage for solving important problems that are currently intractable.”

Microsoft has unveiled a new auto-scaling system that uses Kubernetes to expand or shrink the amount of cloud-computing resources required for machine learning training workloads. The system was developed in partnership with Litbit, a San Jose, Calif., technology startup that uses internet of things data to create "AI Personas" that workplaces can use to augment the capabilities of their employees based on their collective experiences and know-how.

Litbit discovered that AI training workloads loads varied wildly, since customers train their personas at different times. Microsoft and Litbit settled on Kubernetes partly because of its proven cluster management technology, but also because of the strong community support the cloud project had attracted in a few short years.

The auto-scaling system has been running for four months and has enabled Litbit to scale to up to 40 nodes at a time and seamlessly downsize when demand abated.

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