Salesforce enters and gains the main position in the artificial intelligence (AI) and the Internet of Things (IoT) markets. Salesforce is promoting Software-as-a-Service (SaaS). They are adding a Platform-as-a-Service (PaaS) development layer into its SaaS applications. Their SaaS and the value of cloud are successful. Through adding a PaaS development layer to its Saas applications, customers can build their own software solutions to meet their business needs. For example, according to Gartner, the global Saas market size will grow from $46.3 billion in 2017 to $75.7 billion in 2020 and for PaaS market, it will grow revenue from $7.2 billion in 2016 to $14.8 billion in 2020. Additionally, Salesforce’s AI perspective has begun with WAVE analytics platform three years ago and released Einstein AI platform last year. Salesforce recently announced IoT Explorer Edition in order to develop IoT applications quickly. The new Salesforce IoT is based on its Saas platform and enables clients to turn device data directly into customer context. As a result, Salesforce’s new IoT Explorer improve the positioning of its IoT and AI capabilities. IoT Explorer can translate IoT data into its service cloud and other devices.
Do you think Salesforce IoT’s revolution can be a trend in the future IoT cloud services? How do think about Salesforce IoT is the best option for company’s Internet of Things?
Salesforces IoT Strategy by Technewsworld
Salesforce Reshuffles SaaS, PaaS in Internet of Things and AI by Ecommerce times
Salesforce focuses on customer with new IoT cloud service by Internet of Things Institute
The Crystallization of Salesforce’s IoT Strategy by Ecommerce times
Facebook is working on a feature which allows a user to unlock the account and verify identity with a facial recognition. But, do we really shouldn’t be alarmed the privacy of Face ID which related to biometric data? From Dr Michal Kosinski’s article points that “AI will be able to determine people’s political leaning and IQ based on looking at people’s face”. Face-reading AI is able to infer people’s personal information and private data. For example, AI computer program can process amount of people’s online photos from a dating application in order to identify people’s sexual orientation. I think it sounds dangerous for a privacy direction. However, it can help to identify criminals and non-criminals by using facial scans. Relating to class intention, IT creates value when it supports achieving business outcomes. In order to preserve data breach risk, Facebook may need to invest more on company’s monitor. It could define a large project within medium and high risk because clients aren’t quite sure about back-end data privacy protection feature.
Will you use the face-reading feature on your Facebook? In your experience, how do you protect your personal information?
The ERP systems are sort of transforming from heavy complex systems to more accessible, which can through the cloud migration. Although ERPs today are able to capture information historically and measure it for manufacturers, it still faces a challenge to handle all data and capture it in a meaningful way.
An opportunity for improvement is that a bridge between the machine and the ERP. The key to process in the future is going to be automated, thus it would be quicker and more reliable. Additionally, a supervisor does not have to be clocked in or even at the plant. Debbie Krupitzer is as the industrial internet of things practice lead for North America at Capgemini, considers the integration with ERP. The data aggregation is involved that take the data from the sensors or from the manufacturing execution system, then push this back into the ERP piece. I believe that ERP will keep its advantages manage a business and capture its information. On the other hand, the further developing ERP would improve the system and capture some specific information to managers, and get the more efficiency and meaningful information in the future.
Do you believe that the digital transformation process truly transformative?
How to avoid manufacturing ERP implementation failures? How ERP develops to catch up today technology’s needs?