Global Deep Learning Software Market Size By Type (Artificial Neural Network Software, Image Recognition Software, Voice Recognition Software), By Application (Large Enterprises, SMEs), By Geographic Scope And Forecast

Deep Learning Software Market Size And Forecast

Deep Learning Software Market size was valued at USD 2,761.89 Million in 2020 and is projected to reach USD 4,605.37 Million by 2028, growing at a CAGR of 41.70% from 2021 to 2028.

Hey, it looks like deep learning software is really taking off, especially in areas like self-driving cars and healthcare! That's expected to give the whole industry a big boost. Plus, we're seeing this growing demand for more computing muscle, and the fact that hardware is getting cheaper. You see, deep learning algorithms are much speedier on a GPU than a CPU, which is making more and more industries jump on the deep learning bandwagon. If you want the full scoop, check out the Global Deep Learning Software Market report. It's got everythingkey segments, all the latest trends, what's driving the market, what's holding it back, a look at the competition, and all the major things influencing the market. Click here to learn more.

Global Deep Learning Software Market Definition

Deep learning is a subfield of machine learning that consists of a series of computer instructions or algorithms that is inspired by the function and structure of the brain. Deep learning is widely known as artificial neural networks or deep neural networks. Deep neural networks are a set of algorithms that are designed to recognize patterns and are built with components of larger machine-learning applications, which include algorithms for reinforcement learning, classification, and regression. Examples of deep learning applications include driverless cars, voice control in consumer devices, and many others, which help boost the Deep Learning Software Market size.

Deep learning is pretty cool because it can learn from all sorts of data, both structured and unstructured! You see it everywhere now, like in virtual assistants, helping driverless cars see the road, fighting money laundering, and even recognizing faces. Some experts say Google is leading the way in AI, machine learning, and deep learning. Basically, deep learning uses something called a Neural Network to mimic how animals think. This network has three layersthe Input Layer, the Hidden Layer(s), and the Output Layer. Each connection between these layers has a "weight" that shows how important each input is. The best part? If you don't really understand the subject, deep learning is great because you don't need to spend as much time figuring out the right features. It really excels at tough problems like image classification, natural language processing, and speech recognition.

Global Deep Learning Software Market Overview

Increasing applicability in the autonomous vehicles and healthcare industries is expected to contribute to the industry growth significantly. This technology is gaining prominence on account of its complex data-driven applications including voice and image recognition. It offers a huge investment opportunity as it can be leveraged over other technologies to overcome the challenges of high data volumes, high computing power, and improvement in data storage.

Basically, everyone's jumping on the deep learning bandwagon! Why? Because we need more computing power, and thankfully, hardware is getting cheaper. Deep learning algorithms can really blaze through tasks on a GPU compared to a CPU. This speed boost is a big reason why industries are embracing deep learning. Plus, the way deep learning is working its way into big data analytics is only expected to make the Deep Learning Software Market bigger. All those R&D efforts by companies making GPU chipsets? They're just going to fuel the demand for those GPU-powered chips. Take Google, for example – they announced they were launching GPU chips back in early 2017 for their cloud machine learning to make those heavy-duty computing tasks run even faster. GPUs are really taking off as neural networks become more and more important for training deep learning models.

We're seeing tons of data being created across all sorts of industries, and that's really driving growth in this area. Plus, as we need humans and machines to work together more and more, it's opening up cool new opportunities for companies offering better solutions and features. Take aerospace and defense, for example. They're using this tech to tackle tough defense jobs on embedded systems by crunching huge amounts of data. These solutions are helping with image processing and data mining, letting them predict and figure out the best moves forward. Think about this the U.S. Department of Homeland Security even used it in their SEAS project to try and predict what might happen next.

However, lack of technical expertise in deep learning and absence of standards and protocols are the factors that can hamper the Deep Learning Software Market growth as well as the requirement of a large amount of data to train neural networks is expected to pose a challenge to the industry growth.

Global Deep Learning Software Market Segmentation Analysis

The Global Deep Learning Software Market is segmented on the basis of Type, Application, And Geography.

Deep Learning Software Market, By Type

• Artificial Neural Network Software• Image Recognition Software• Voice Recognition Software

Based on Type, The market is bifurcated into Artificial Neural Network Software, Image Recognition Software, and Voice Recognition Software. The image recognition segment dominated the industry in 2016, capturing a revenue share of over 40%. One of the most widely used applications of this technology includes Facebook’s facial recognition feature. It is widely used to recognize patterns in unstructured data including sound, text, images, and videos.

Deep Learning Software Market, By Application

• Large Enterprises• SMEs

Based on Application, The market is segmented into Large Enterprises and SMEs. The large enterprise segment is anticipated to dominate the Machine Learning Market with a significant market share due to the growing adoption of machine learning to extract the required information from a large amount of data and forecast the outcome of various problems.

Deep Learning Software Market, By Geography

• North America• Europe• Asia Pacific• Rest of the world

Based on Regional Analysis, The Global Deep Learning Software Market is classified into North America, Europe, Asia Pacific, and Rest of the world. North America dominated the Deep Learning Software Market with a revenue share of over 45% in 2016, which is attributed to increased investments in artificial intelligence and neural networks. The high adoption of image and pattern recognition in the region is expected to open new growth opportunities over the forecast period. Moreover, the region is one of the early adopters of advanced technologies, rendering organizations adopt deep learning capabilities at a faster pace.

Key Players

The “Global Deep Learning Software Market” study report will provide valuable insight with an emphasis on the global market. The major players in the market are Microsoft, Express Scribe, Nuance, Google, IBM, AWS, AV Voice, Sayint, OpenCV, and SimpleCV. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

Key Developments

Okay, so here's the dealback on June 24, 2021, Oracle and Deutsche Bank (you know, one of the biggest banks out there) announced they're teaming up for a few years. What's the plan? To give Deutsche Bank's database tech a serious makeover and speed up their digital game. Deutsche Bank is going to be upgrading their current database systems and moving most of their Oracle Database stuff over to Oracle Exadata Cloud @ Customer. Think of it as a way to use Oracle Exadata Cloud Service, but on their own terms, which is key for apps that either can't move to the public cloud or might later on. This will give them a dedicated space to really focus on, well, everythingtrading, how payments go through, figuring out risk, doing financial planning, and even making sure they're following all the rules and regulatory reporting.

Hey, guess what? On August 4th, 2021, Amazon Web Services Inc. made its AWS Contact Center Intelligence even better! They've added a new mobile analytics tool that really promises to help us understand what's going on in customer conversations. Amazon calls it Amazon Transcribe Call Analytics, and it's like a chat learning curriculum that you can enable yourself. It's built to play nice with the Amazon Transcribe tool you might already be using to turn customer service calls into written transcripts. Julien Simon, Amazon's "evangelical literacy evangelist" (cool title, right?), wrote in a post that even a simple phone call with a new or existing customer is a goldmine for learning about what they really need. We absolutely shouldn't let those opportunities go to waste!

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Reasons to Purchase this Report

We'll dive deep into the market using both qualitative and quantitative methods, looking at segmentation through economic lenses, but also considering other important factors. You'll get market value data (in USD Billion) for every segment and sub-segment, plus we'll pinpoint the region and segment poised for the fastest growth and market dominance. Our geographical analysis will highlight product/service consumption, revealing the factors influencing each region's market. We'll map out the competitive landscape, showing the market ranking of key players alongside their recent launches, partnerships, expansions, and acquisitions over the past five years. Company profiles will be extensive, covering overviews, insights, product benchmarking, and SWOT analyses for the major players. Expect a look at the industry's current and future outlook, considering recent developments, growth opportunities, drivers, and challenges in both emerging and developed regions. We'll also give you an in-depth analysis through Porter's five forces and provide market insights through a Value Chain perspective. Finally, we'll explore the market's dynamics, identifying growth opportunities in the years ahead, and include 6 months of post-sales analyst support to help you make the most of it.

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