[1] Today,
Google released a blog post announcing some key changes to Password Manager. The new changes will enable users with multiple passwords for the same sites or apps, to group them on Chrome and Android devices automatically.
At the same time, when entering passwords into online accounts, a feature called Password Checkup will warn users about
compromised credentials and weak or reused passwords and give them an option to change them. This means that users will have the opportunity to automatically secure weak passwords that put them at risk of being hacked.
In addition, the changes will enable users to create strong,
unique passwords across platforms. Users on Android will also be able to create a shortcut to Password Manager on their home screen so they can access their passwords with a single tap.
>> Read more. [2] Most organizations working on
artificial intelligence (AI) and advanced analytics projects tend to use data from existing systems like Google Analytics and CRMs. These sources offer plenty of information to work with, but they are also disparate in nature, which means the data they provide comes with varying structures (imagine different field types) and different levels of granularity, quality and completeness.
This makes it difficult for the organization to use the data as-is. It also adds to the technically challenging and time-consuming element of
data wrangling – where teams have to work to clean, organize and transform the data into a standardized format for use. Plus, it also creates compliance issues, since it's difficult to track data lineage from a collection of black-box SaaS applications.
To solve the problem, London-based Snowplow Analytics is offering enterprises a platform to generate structured behavioral data assets (describing the behavior of customers, the actions and decisions they make, and the context of those actions and decisions) that are customized to suit specific
AI and BI applications and remain fully compliant at the same time.
>> Read more. [3] This year, John Deere debuted a
fully autonomous tractor, powered by artificial intelligence (AI), that's ready for large-scale production.
According to a press release, the tractor has six pairs of stereo cameras that capture images, and pass them through a
deep neural network. It then classifies each pixel in approximately 100 milliseconds and determines if the machine continues to move or stops, depending on if an obstacle is detected.
John Deere's efforts in developing AI solutions are part of
a larger trend across the agricultural landscape. Spending on agricultural AI technology and solutions is predicted to grow from $1 billion in 2020 to $4 billion in 2026, according to Markets & Markets.
>> Read more. 
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