Thomas J. Watson Sr. joins Computing-Tabulating-Recording Company (CTR) in 1914 and over the next two decades transforms it into a growing leader in innovation and technology. He built a worldwide industry; it is called to International Business Machines Corporation (IBM) in 1924. According to Fortune 500, IBM is ranked as one of top 10 firms in 90’s. Let’s take a look at the roadmap of the IBM in the digital transformation, it consists not just software, hardware and services include cognitive solutions and cloud platform. IBM’s Bekas explains that we simply can’t scale enough hardware to solve this. “Ultimately, hardware can’t beat computational complexity. You need to have a combination of algorithmic improvement and hardware development,”
In this article, we will focus on artificial intelligence area and related industry focuses. Artificial intelligence is rapidly coming of age, poised to transform businesses and industries globally. The market for AI is on an exponential growth curve and is expected to reach $16.06 billion by 2022. With over half of all developer teams projected to embed AI services in their apps by 2018, it’s inevitable that consumers will soon be interacting with these new technologies on a regular basis.
On the IBM’s AI Strategy (*)
With the highest level of intelligence that exists in technology systems, these solutions tackle challenges ranging from answering client inquiries to helping physicians fight cancer. Watson Health optimizes performance, engage consumers, deliver effective care and manage the health of your population.
Cognitive systems, IBM’s Watson, are not programmed; like humans, they learn from experts and from every interaction, and they are uniquely able to find patterns in big data. They learn by using advanced algorithms to sense, predict and infer. Doing so, they augment human intelligence, allowing individuals to make faster and more informed decisions.
The first cognitive system was Watson, which debuted in a televised Jeopardy! (a quiz competition) challenge where it bested the show’s two greatest champions. Watson answered many questions about synonyms, antonyms or slang and it achieved all of them without the internet connection. To find and understand the clues in the questions use machine learning, statistical analysis, and natural language processing. Also, you can watch Watson’s performance on Jeopardy! New generations of that cognitive systems are trying to use diagnose oncology for healthcare professionals and in the customer services. Watson solutions are being built, used and deployed in more than 45 countries and across 20 different industries. IBM unceasingly pushes the boundaries of Watson increasing its use areas and developing new algorithms.
In earlier 2017 IBM announced the cooperation with Illumina Inc., their new designs’ aim is helping standardize and simplify genomic data interpretation. TruSight Tumor 170 is an assay designed to cover 170 genes associated with common solid tumors by Illumina. In a matter of minutes, Watson for Genomics will read the genetic alteration files produced by TruSight Tumor 170, comb professional guidelines, medical literature, clinical trials compendia, and other sources of knowledge to provide information for each genomic alteration, and produce a report for use by researchers — a process that typically takes scientists more than one week to complete. Watson for Genomics ingests data from approximately 10,000 scientific articles and 100 new clinical trials every month.
IBM’s technology is quite unique thanks to highly adaptable intelligence systems, protect and respect client data, trained in domain depth and transformational services.
IBM’s Watson services based on four main parts as language, speech, vision, and data insights.
- In the language part, the conversation is maintained by chatbots that understand natural language and deploy them on messaging platforms and websites, on any device. Document conversation, language translator, tone analyzer, and natural language translator are used and information retrieval is enhanced with machine learning. Also, Natural Language Processing (NLP) has a long and distinguished history at IBM Research and is currently the focus of numerous projects worldwide. IBM interests cover a wide range of topics from Machine Translation, to Information Extraction, to Question Answering. Artificial intelligence tries to understand personality characteristics, needs, and values in written text.
- Watson Speech to Text converts audio voice into written text. This system transcribes calls in a contact center to identify what is being discussed, when to escalate calls, and to understand content from multiple speakers. Speech to text creates voice-controlled applications — even customize the model to improve accuracy of the language and content you care about most such as product names, sensitive subjects, or names of individuals. Furthermore, IBM enables computers to speak like humans via converting written text to text into natural sounding audio. The common areas that used are; toys for children, automate call center interactions, and communicate directions hands-free.
- Visual Recognition understands the contents of images — visual concepts tag the image, find human faces, approximate age, and gender, and find similar images in a collection. You can also train the service by creating your own custom concepts. It is usually used in the e-commerce sites to detect a dress type. According to February News , a new capability being added to Visual Recognition is color tagging. While Watson has already been able to detect color, it will now return the top colors it sees in each image as response tags, each accompanied by a classification score. The new capability allows users to quickly assess the dominant color schemes within an image and turn these into actionable insights. Not only analyze, fashion designers will predict color trends from ten years of fashion runway images.
- With AI, convert, normalize and enrich your unstructured data. Discover from already exist pre-enriched datasets by using a simplified query language like Discovery News dataset is a public data set that has been enriched with cognitive insights, and is included within the Watson Discovery Service. It is updated continuously, with over 300,000 new articles and blogs added daily, sourced from more than 100,000 sources.
If we consider ABB and IBM collaboration from, organizations using the solutions will benefit from ABB’s deep domain knowledge and extensive portfolio of digital solutions combined with IBM’s expertise in artificial intelligence and machine learning as well as different industry verticals. ABB and IBM will leverage Watson’s artificial intelligence to help find defects via real-time production images that are captured through an ABB system and then analyzed using IBM Watson IoT for Manufacturing. Previously these inspections were done manually, which was often a slow and error-prone process. By bringing the power of Watson’s real-time cognitive insights directly to the shop floor in combination with ABB’s industrial automation technology, companies will be better equipped to increase the volume flowing through their production lines while improving accuracy and consistency. As parts flow through the manufacturing process, the solution will alert the manufacturer to critical faults — not visible to the human eye — in the quality of assembly. This enables fast intervention from quality control experts. Easier identification of defects impacts all goods on the production line and helps improve a company’s competitiveness while helping avoid costly recalls and reputational damage. 
All these R&D and acquisitions are claimed that cost $16bn during 2016 but Watson would start bringing in money despite all cost. IBM’s chief financial officer Martin Schroeter said revenue would come through Watson serving IBM’s strategic imperatives and cognitive software. Watson is the “silver thread” running through Watson Health and Financial Services, IBM’s IoT and security, he said. “Watson is firmly established as the silver thread that runs through those cognitive solutions and you can see all of that in the solution software performance.”
Strategic imperatives accounted for 40 percent of IBM’s revenue, $32.8bn for 2016, the firm said. Its stated goal is to make $40bn from them by 2018.
Industry Focus: As IBM brings higher levels of value to its clients, as its offerings are being built for the needs of individual industries. Healthcare and Financial Services are two examples of the company’s initial cognitive focus. In the healthcare industry, IBM Watson achieves remarkable outcomes, accelerate discovery, make essential connections and gain confidence on their path to solving the world’s biggest health challenges.
One year ago from today, IBM announced their plan to acquire Truven Health Analytics, a leading provider of cloud-based healthcare data, analytics and insights for $2.6 billion. Other industries are cyber security and financial guidelines IBM Security — which monitors 35 billion security events a day for 12,000 clients spanning 133 countries — launched the world’s first commercial “cyber range,” where clients can simulate and prepare for real-world attacks and draw on the power of Watson to fight cyber crime. The company told The Telegraph that IBM Watson “can help thwart the major hacks that have become a growing concern”, quoting attacks on Yahoo, Lloyds and TalkTalk. Watson’s security machine can additionally save up to 20,000 hours a year chasing false alarms.
Blockchain will enable financial institutions to settle securities in minutes instead of days; manufacturers to reduce product recalls by sharing production logs along their supply chain; and businesses of all types to more closely manage the flow of goods and payments. Blockchain brings together shared ledgers with smart contracts to allow the secure transfer of any asset — whether a physical asset like a shipping container, a financial asset like a bond or a digital asset like music — across any business network. IBM is working with companies ranging from retailers, banks, and shippers to apply this technology to transform their ecosystems through open standards and open platforms.
In April 2017 National University of Singapore (NUS) School of Computing and the IBM Innovation Center for Blockcha (ICB) are collaborating to develop a module on fintech. The aim is to enhance students’ knowledge and skills. Blockchain is a fast growing area across the globe, with banking, healthcare and the government leading the way in terms of adoption.
“Blockchain is one of the most disruptive technologies in computing today, and it is impacting many industries including financial services, trade, healthcare, and supply chain. This collaboration with the National University of Singapore School of Computing will help prepare a future workforce that is born on blockchain, ready to implement, improve and innovate: core skills required for Singapore to achieve its vision as a Smart Financial Centre and Smart Nation,” said Robert Morris, Vice President Global Labs, IBM Research.
IBM’s PowerAI system use combination of deep learning, machine learning, and AI and deploys a fully optimized and supported platform for your business.
Other Recent Strategic Mergers and Acquisitions:
A strategy based on hiring experts of a relative area and gain power from cooperates.
‘Build a network of like-minded people, whether it is a digital community or an in-person one. Establishing your network and growing your connections is vital to becoming a new collar worker.’
– Randy Tolentino, Software Developer, Austin, TX.
February 17: IBM has acquired the world’s largest security company Agile 3 Solutions as the part of the IBM Data Security Services. Besides the merging, IBM has also closed the acquisition of Ravy Technologies, a subcontractor to Agile 3. IBM Security has invested approximately 1,900 security experts since 2015. That tech offers one of the most advanced and integrated portfolios of enterprise security products and services. It protects your data against internal and external threats and the innovative new technologies are designed to fight cybercrime by these cooperates.
April 17: The combination of digital solutions-artificial intelligence-machine learning. New solutions aim to bring real-time cognitive insights to the industry. AI does not just simply gather data, will help eliminate inefficient processes and redundant tasks to understand the actions. Using data will be more sense and reasoning for the cognitive computing of IBM.
-The era of cognitive systems
The sectors have already used or planned on using of cognitive systems are analyzed according to for all users like that:
May 17: Mark III Systems’ Cognitive Call Center platform transforms the traditional call center model by using IBM Cloud and Watson to help agents identify, filter, analyze and take actions on inbound and outbound calls. The platform uses IBM Cloud Object Storage to manage the unstructured data, and it uses Watson APIs, specifically Watson Speech to Text and Watson Tone Analyzer, to automate the transcription and tagging of audio, provide near real-time analytics and actions and enable deeper analytics for audit situations. IDC estimates that by 2020, global spending on cognitive and AI will be more than $46 billion.
IBM AI HISTORY RESEARCH
IBM has been a leader in AI research since the field’s early days in the 1950s, when Arthur Samuel developed a checker player that learned from experience. In 1961 he put his program up against the Connecticut state checker champion, the number four ranked player in the nation. His checkers program won. This work was one of the earliest and most influential examples of machine learning. Forty years later, IBM Research’s chess-playing program Deep Blue made history when it beat Gary Kasparov, becoming the first chess-playing program to defeat a reigning world champion. We continue to take on new challenges, including Jeopardy! and Go. Summarily here the list of IBM’s contributions to AI:
Deep Blue — Computer Chess (1997):
IBM chess machine Deep Blue defeated World Chess Champion Garry Kasparov in a six-game match. Thanks to Its successful algorithms, Deep Blue’s victory has a fundamental part of the AI history and development.
‘In the early 1990’s, IBM Researcher Gerry Tesauro demonstrated that reinforcement learning (RL), hitherto regarded as a mere theoretical curiosity, could achieve spectacular success in complex real-world problems. The ensuing intense interest led to RL becoming one of the most important areas of machine learning research, particularly for tasks requiring automated decision-making. Using “temporal difference” RL combined with a neural network, TD-Gammon played millions of games against itself, in the process developing a level of play on par with world champion human backgammon players. Considering that it started from a completely random initial strategy, used only the raw board state (with no hand-crafted features), and used only the binary win/loss signal at the end of the game to guide its learning, this result shocked the machine learning world.’
RL in real-world domains including elevator control, production scheduling, network routing, financial trading, spoken dialog systems, power plant control, and video game AI.
Infomax Principle for Neural Network Learning:
Ralph Linker’s discovery that a standard (Hebbian) learning rule, combined with locally correlated random activity, causes a model visual system network to automatically form “neurons” that respond selectively to light-dark edges having a preferred orientation, and to organize a layer of these neurons
The infomax principle addresses a general feature of biological information processing — the brain’s ability to learn automatically to recognize visual, auditory, and other features present in the environment.
[*] Summarized from the IBM Annual Report 2016
All cooperation news are taken from: https://www-03.ibm.com/press/us/en/index.wss