Teradata accuse SAP en justice d’avoir développé HANA en utilisant sa propriété intellectuelle et d’essayer à présenter d’empêcher ses clients d’accéder à leurs données ERP.
Source de l’article sur ZDNet
With software engineering being in such a fast-paced environment, traditional project management approaches are no longer viable. That means that IT professionals must find new ways to handle frequently changing development tasks.
Sharing this idea and focusing on the existing incremental development techniques, 17 software specialists introduced the Agile project management philosophy in 2001. Principles of flexible, fast, and collaboration-centered software development were outlined in the Agile Manifesto.
Ethical and Regulatory Questions Facing AI
At work, as part of a reading group, I had the chance to spend some time reading about some challenges facing AI regarding ethics and regulation. Despite having worked with and thought about AI and Machine Learning before, I hadn’t spent much time thinking about the ethical and legal challenges facing the field, so it was a lot of fun to do some reading in the area. I was mostly interested in the more short-term challenges of the space in the coming years, so I didn’t get into the more long-term concerns about things like Artificial General (Super) Intelligence or weaponized AI.
Regardless of area of expertise, most of us are probably already aware of the momentum around Artificial Intelligence (AI). Between self-driving cars, home assistants (Alexa, Google Home, et al.), and the growing capabilities of our mobile devices, there is no escaping the ever looming presence of AI in our lives.
Our second SnapLogic Technology Open House had a bit of a twist to it, which I’ll get to later. I’m pleased to say we had a good 40+ attendees joining us from around the Bay Area. To start things off, I introduced some of our innovation projects and spoke about the origins of Iris technology, which was originally just a research project.
Next, the story of SnapLogic’s Iris AI was presented by Jump Ananpiriyakul, our machine learning expert. Jump’s presentation, “Cooking with AI/ML at SnapLogic” highlighted the journey of Iris through the lens of cooking the famous Thai dish, Tom Yum Kung. During his presentation, Jump gave an overview of the SnapLogic Platform and a live demo that showcased exactly how Iris AI and the Enterprise Integration Cloud works. He also showed how we use our own platform in the construction of machine learning models. Hearing him talk about how Iris is being used today and about the potential future applications of AI was a definite highlight for a lot of our guests.
Over the years a lot has been done to enhance the control and efficiency of application development processes. From Agile development to change management solutions based on ISO and ITIL standards, the progress has been remarkable. However, like everything else, this, too, has a downside. They say that every cloud has a silver lining, but in the world of technology, this silver lining is likely to affect the functionality of the cloud. The increase in the use of Agile development has aggravated the pressure IT organizations face in deploying new applications.
Each new enterprise application brings in several diverse application components spread across numerous environments, including application servers, desktops, Web servers, mobile devices, databases, etc. Also, most large organizations have different departments handling each of these functions, and the potential product users are often not in control of the timelines. Besides, since security and compliance requirements put a lot of burden on the IT teams, companies adopt a "better safe than sorry" approach and discourage employees from easily getting new applications or their versions. For the product vendor, the total cost of support is directly proportional to the number of older versions out there in the field.
QISKit ACQUA Bridges Classical, Quantum Computing
Working with real quantum computers just got easier for experts in chemistry, artificial intelligence, and optimization. Building on QISKit, our open source quantum information science kit for software development, we’ve released ACQUA — Algorithms and Circuits for Quantum Applications. This new open source software allows classical computer applications to send complex operations to be run on quantum computers, over the cloud.
Let me start by explaining the quantum software stack, and where QISKit and ACQUA fit. At the lowest level is the hardware where the qubits sit at the very cold temperature of 15 mK. The qubits receive microwave pulse signals for a calculation, which have been translated and converted from OpenQASM, IBM Q’s low-level assembly language, by QISKit. Users of the free IBM Q Experience 16 qubit system can write programs directly in OpenQASM, but it’s easier to use libraries in higher level languages. That’s where QISKit comes in. It’s a front-end interface that works with Python (read IBM Fellow Dr. Jay Gambetta’s article about QISKit’s recent upgrade).
A confession: when someone emails to a large technical list a "simple" question, I’ve sometimes in the past felt a sense of "How can you not know this? Everyone knows this! We solved this in 2004!" But of course, everyone can’t possibly know even "the basics"; there’s no such thing as "herd knowledge" among software developers. There’s no "All Developers Everywhere" mailing list (thankfully), and there’s no monthly "Developer’s Journal" which new grads are forced to pore through until they’re fully caught up (again, for the best I expect).
There’s also no getting around the fact that 2004 is starting to feel like a very long time ago — we’re closer to 2030 than 2004 even now, and people born in 2004 will be starting Comp Sci degrees all too soon.
Machine learning, data science, and data analytics or scientists are emerging fields growing into various sub-fields, helping companies improve their efficiency and performance at certain stages during the operations and services. Hence, understanding these technologies is very important to realize their right use and benefits into various sectors. So, here we have discussed what data science is and what is machine learning with few sets of examples.
What Is Data Science?
A community is only as strong as its contributors. Whether you’re at the top when it comes to user engagement, or you’re at the bottom struggling to excite your users to participate, here are 13 tips to help you improve engagement and foster a mentality of sharing.
1. Create Exclusivity
Who doesn’t like being rewarded for their work? (obviously a rhetorical question!) Everyone likes to be rewarded for their work, and your community is no different. To successfully run a community your members need to be engaged, sharing, and collaborating. To encourage participation, create exclusivity for your best users. Options to do so could be sending them a swag pack, creating a beta preview of your upcoming software release, sending them conference tickets, or inviting them to your headquarters. The opportunities are endless, so be creative.
