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ZDNet explores the way AI, the cloud, and Big Data in “the AI regeneration era”. The industry dubbed the adjacent infrastructure stack Industry 3.0. Due to the new generation of AI chips, data-centric software tasks should benefit in terms of both operational databases and analytics, as well as in what machine learning (ML) implies.

The easier way of handling Big Data can make companies of all sizes and from any location access new operational horizons. But organizing Big Data processing still involves a series of key decisions, which often call for experienced consultants. The pharmaceutical companies have a number of hard choices in the cloud and on-premise already laid out for them.

Bear in mind that the LASTING Software implementation of analytical algorithms and engines for statistical analysis is at the base of the world leading, FDA-approved solution. Our solution is being used by 93% of the world’s pharmaceutical companies. We will therefore walk you through the main expected pharma industry challenges, inspired by the article we mentioned.

 

The importance of processing units in accelerating your software workloads

It’s more exactly about GPUs – Graphical Processing Units, the ones that “leverage parallelism” and better keep up with Moore’s law. Their architecture responded to the new challenges well, and now one of the GPU main producers (NVIDIA), announced a set of innovative products with a new architecture.

Hardware to match the upgraded modern request is therefore on the way. But the software is also of importance. Seeing how “how GPUs are currently the AI chip of choice for ML workloads”, the ML libraries come into play.

For detailed recommendations, you may access the original article. What you need to remember is that “GPUs can greatly accelerate workloads that can be broken down in parts to be executed in parallel”. Enough said.

 

Field Programmable Gateway Arrays and their software scope

FPGAs, simplistically describable as “boards containing low-level chip fundamentals, such as AND and OR gates” are not new. Specific tasks or applications find their correspondence in the hardware description language (HDL) that specifies the FPGAs’ configuration.

Changing the said configuration at need suffers from a certain software layer immaturity. This time, the player that stands out is Intel. By investing into FPGAs R&D, this company tries to catch up on GPUs with a new line of next-gen FPGAs.

Again, the software is crucial. Along with it, the databases and libraries need to support the FPGA-accelerated analytics.  

 

Once having decided what you want, different choices ensue

To quote our inspirational article of the week: “Should you build your own infrastructure, or use the cloud? Should you wait until offerings become more mature, or jump onboard now and reap the early adopter benefits? Should you go for GPUs, or FPGAs? And then, which GPU or FPGA vendor?”

You may check some of the details and possible answers put forth by the author.

If you can make sense of them, or even get the big picture, then you must be familiar with both hardware and software – kudos to you.

Even so, the activity of your company might need the time to focus on different matters. You can still use a partnership where you can state what you need, infrastructure-wise, and your software solutions partner would deliver it.

Unable to follow the detailed options presented by ZDNet? Then the assumption that your company is a typical pharmaceutic industry entity could be the right one. No need to get stuck trying to learn software-specific notions or trying to make sense by yourself what would the best hardware elements be.

 

The multitude of available options pushes for the right partnerships. The wisest, poised for efficiency and success organizations learn to delegate tasks. To make next-gen digitization simple and get right to the point where you benefit from it, find the right software solutions partner.

We are waiting for your email or call!

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Tech

LASTING Software has over 100 man-years experience in delivering automotive 2D & 3D graphics engines and graphical interfaces for high-profile Tier 1 customers.

Our software engineers are capable of creating a Graphics Engine adapted to any embedded display. Our expertise in automotive HMI/GUI (Human Machine Interface/Graphics User Interface) development services includes, but is not limited to:

  • IVI (In-Vehicle Infotainment) HMI,
  • cluster HMI,
  • graphics engine customization,
  • graphics SDK (Software Development Tool Kit) development, and more.

 

 

Automotive industry trends point out revolutionary innovations

 

We also keep updated on the latest trends in the automotive industry. The auto industry is on the verge of transformation, which triggers the accelerated rise of new technologies. Most of the big industry players are aware of these game-changing disruptions and prepare for the upcoming imminent changes. Diverse mobility, autonomous driving or car connectivity all experience high and low scenarios. Both versions lead to the same destination, only at different speeds.

We’ve selected a McKinsey study that shows the expected trends on the market by 2030, as a more detailed illustration of this future perspective.

As you may see below, in one image from this study, the leading OEMs will compete on multiple fronts:


We feel that we are the right partner for success in this competition, in what your software development needs are concerned.

 

The need for leading-edge development services

 

Taking the industry trends into consideration is one way to go when developing a viable strategy for the future.

Another approach would be logically anticipating what the main trends would involve. In a connected world, the modern means of transportations need to function seamlessly, securely and in a synchronized manner. Such standards are achievable only through the most efficient software development processes.

Knowing and following the coding standards, choosing the best methodologies, combining technical expertise with the capacity to innovate per request are just a few must-haves.

Take autonomous vehicles. Here is an article that illustrates how autonomous cars “see” the world. The complexity of the environment is matched by the one of the autonomous vehicles. From real time sensory equipment to the object identification processes and analytics software – it’s all a fascinating and impressive micro – world.

We can’t wait for these exciting perspectives to become reality and we are proud to be part of the process.

 

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