Redefining Ai Ibm Watson S Vision Beyond Mimicking Human Intelligence
Part of the book series: Algorithms for Intelligent Systems ((AIS)) IBM Watson the so-called genius supercomputer that can supposedly assist doctors in treatments of their patients, too hyped or a groundbreaking technology? The following project analysis of IBM Watson, more specifically Watson for heath, has been described using materials from both IBM documents itself and reviews by third parties. Emphasis on both early and recent failures and inaccuracies have been mentioned, and solutions with regard to the context of the mentioned issues have been proposed. Going further, facts and even hypothetical situations will be discussed in regard to the above proposed question, what is IBM Watson? How exactly does it work?
Is it really as good as IBM claims it to be? Is it really going to help completely revolutionize the AI world? Finally comes the comparative analysis of IBM Watson’s competitors to take a look at how they differ and which one is better. With technology there is always room for growth and enhancement. Toward the end will Watson prove itself to be worth all the public and mainstream media attraction? Or will it turn out to be another overhyped AI technology?
This is a preview of subscription content, log in via an institution to check access. Tax calculation will be finalised at checkout IBM100 A computer called Watson. IBM, [online]. https://www.ibm.com/ibm/history/ibm100/us/en/icons/watson/ In today’s rapidly evolving technological landscape, artificial intelligence (AI) is making incredible strides, yet there’s a prevailing notion that to succeed, we must replicate human cognitive processes within a digital framework.
However, Rob High, IBM’s Chief Technology Officer for Watson, offers a contrasting perspective, arguing that true value doesn’t lie in emulating human intellect but rather in enhancing it. The insights from High during an interview at MWC challenge conventional thinking about AI and pave the way for the next generation of intelligent systems. High acknowledges the proliferation of voice-activated devices with: However, he is not overly impressed with the capabilities of the current generation of chatbots. He describes existing interactions as fundamental “command-and-response” models, which, despite their growing popularity, lack depth and understanding. This is largely due to their simplistic nature, where conversations are broken down into isolated utterances rather than meaningful exchanges.
IBM Watson is designed to tackle the shortcomings of basic chatbots, introducing a more nuanced approach to dialogue. High emphasizes that the company’s focus is on creating systems capable of frame-based dialoguing — an advanced structure that allows users to interact by exploring options and engaging in back-and-forth conversations. He believes that with this innovation, AI can begin to mimic the complexity of human discussions more effectively, adding a layer of reasoning that is essential for valuable interactions. At the core of High’s philosophy is the realization that understanding a person involves more than recognizing words—they are often guided by implicit motivations. High reflects that while much of AI development has centered on translation and recognition techniques through deep learning, these methodologies still falter in grasping what users genuinely want to achieve. He proposes that focusing on human motivations could lead to breakthroughs in AI performance, driving more effective solutions than merely replicating human cognition.
Digital ecosystems are dynamic and constantly evolving networks formed by independent actors interconnected through digital technologies (Kolloch & Dellermann, 2018). Digital ecosystems include a broad range of co-creators, extending from traditional participants (i.e., customers and suppliers) to online communities (Magistretti et al., 2019). Within such ecosystems, technology's role is shifting. Troshani, Janssen, Lymer, and Parker (2018) researched how traditional business-to-government reporting is being eliminated, and how digital reporting is determined to replace it in light of the challenges to reduce administrative burdens without compromising... Other authors researched the role of using technologies/datasets/tools in DT such as big data and analytics (e.g., Battisti, Shams, Sakka, & Miglietta, 2020; Brous & Janssen, 2020; Caputo, Cillo, Candelo, & Liu, 2019; Carrero,... This cluster contains papers that aim to develop the link between dynamic capabilities and DT, particularly from a theoretical point of view.
Kane (2019) proposed a three factor model for successful digital transformation, based on navigating the digital disruption, rethinking leadership and talent, and becoming a digital organization. Scholars recognised that digital technologies can make a difference in achieving competitive advantage (Helfat, 2000; Afuah, 2002; Pavlou and El Sawy, 2010; Allred et al., 2011; Koch and Windsperger, 2017; Mikalef and Pateli, 2017;... Coherently, the firm’s digital strategic posture is the result of the awareness and responsiveness of the competitive environment (Mithas, Tafti, and Mitchell, 2013). Cenamor et al. (2019) found that platforms can be key growth drivers if SMEs are able to develop digital platform-related capabilities. According to Magistretti et al.
(2019), AI is likely to become a complementary tool for decision-making in SMEs. Together with digitalization, environmental sustainability is a key growth path for firms in the contemporary economy. At the Vogue Women of the Year 2017, IBM Watson used its smart IoT integration and Personality Insights API to create an LED-embedded saree that based on the contest’s winner’s dominant personality traits, changes... Watson had co-created the gala dress for the same event along with Marchesa in 2016. Watson analyzed the twitter tweets on the event and as per the emotions gathered from the tweets it changed the color of the dress. Did you know another fantastic story that IBM Watson was incepted to win the quiz show Jeopardy?
Watson did surprisingly well then the human competitors in the quiz. Are you aware that it can process 40 million documents in 15 seconds? But now let’s see how IBM Watson is changing the world as we know. Watch this Artificial Intelligence Tutorial for Beginners video Have you as a business owner tried to comb through vast amount of previous data so that it is helpful in the current scenario? IBM Watson can be helpful in this regard.
Barristers for example can go through hundreds of older cases which can be helpful in their current case. They can go through all the arguments of older cases and be better prepared. The text in your speech, emails, and social media is used by Watson to depict the being of a person. Through this it can not only make sense of what you did previously but also gauge the way you interact with people and to certain situations. It’s labor intensive and quite hard for HR professionals to analyze the people who are applying for specific roles because of short time and low budgets. IBM Watson is a step ahead in this game in that it analyzes the already working employees chooses those applicants who are best fit to the team.
To make agricultural production more efficient IBM Watson can help in analyzing weather data. Conclusions can be drawn by gauging the past data and future can be accurately predicted. You can lose weight by consuming those food items suggested by Watson. 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,”
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