Ethereum’s new high, a new blockchain venture, Chrome’s counter deceptive extension and more in today’s top stories around machine learning, blockchain, and data science news.
Ethereum, the third largest cryptocurrency by market value soared to new records on 5th January ’18. Ethereum prices rose above $1,000 per unit on early Thursday for the first time ever. Bitcoin investors are increasingly looking towards alternative currencies such as Ethereum, Ripple, and Litecoin, which could be one of the reasons for the rise in price. Following this news, renowned bankers such as Credit Suisse, Barclays, and UBS announced plans to test the Ethereum blockchain in the hopes of making it easier to meet new European Union reporting standards under the Markets in Financial Instruments Directive II.
Apart from this, investors have also helped push up the price of another rival cryptocurrency, Ripple, in part because more banks and institutions agreed to partner up with its community in a bid to speed up transactions, and growing investor interest. Ripple has overshadowed Ethereum’s recent surge outranking the latter’s $100 billion value by nearly $40 billion and now ranks as the second largest cryptocurrency by market capitalization, according to CoinMarketCap.
Google Chrome plans to expand its abuse protection capabilities to further reduce user harm. Chrome will upgrade their automated inline installation abuse detection to improve their detection speed which would better detect extensions using deceptive or confusing installation flows. This implementation is expected to start in a few weeks.
Additionally, this expanded enforcement will also use machine learning to evaluate each inline installation request for signs of deceptive, confusing, or malicious ads or web pages.
On finding any of those malicious signals, Chrome would selectively disable that one inline installation request and redirect the user to the extension’s page on the Chrome Web Store. This selective enforcement will not impact inline installation of that extension from other, non-deceptive sources.
To know more about this new implementation by Chrome visit Inline Installation Enforcement FAQ.
Datametrex AI Ltd and its San Francisco based joint venture partner Bitnine Global Inc. plan to spin out a joint venture entity Graph Blockchain Limited. Graph Blockchain leverages graph database and blockchain technology and provides a unique way of organizing, analyzing and displaying blockchain transactional data in real-time. It presents Blockchain data up to 1,000 times faster than traditional methods from 7- 7000 transactions per second. It can effectively store, manage and present Blockchain transactions specifically in peer to peer networks making it ideal for Fintech, Banking and other mission-critical environments. Graph Blockchain has a contract with Revive Therapeutics Ltd. to develop the blockchain component in Revive’s proprietary patient-focused program.
Google Cloud announced the beta release of preemptible GPUs on 5th January 2018. Users can now attach NVIDIA K80 and NVIDIA P100 GPUs to Preemptible VMs for $0.22 and $0.73 per GPU hour, respectively. This is 50% cheaper than GPUs attached to on-demand instances. Preemptible VMs are highly affordable, short-lived compute instances suitable for batch jobs and fault-tolerant workloads. Last year, Google introduced lower pricing for Local SSDs attached to Preemptible VMs, expanding preemptible cloud resources to high-performance storage. Preemptible GPUs should be a good fit for any fault-tolerant machine learning workloads and other computation-heavy workloads. With Preemptible GPUs customers can now harness the power of GPUs to run distributed batch workloads at predictably affordable prices.
Resources attached to Preemptible VMs have two key differences as compared to the on-demand resources. The Preemptible VMs can be used for a maximum of 24 hours and the compute Engine may shut them down after a 30-second warning.
Customers can simply append –preemptible to the instance create command in the cloud to get started. Alternatively, they can specify scheduling.preemptible to true in the REST API or set Preemptibility to “On” in the Google Cloud Platform Console and then attach a GPU as usual.
Deepsense.ai have trained a team of UN analysts in image recognition and other deep learning areas to help UN leverage its competencies in the field of artificial intelligence. The workshop consisted of a theoretical part and a hands-on coding session to teach participants advanced topics in the field of image recognition. This session was a follow-up of the workshop on text analysis which happened in 2016.
UN and its stakeholders want to leverage data analytics, NLP, translation and cognitive computing to gain deeper insights into global macroeconomic and social trends. Which was why they invited deepsense.ai to share its expertise in the fast-evolving AI field.