Innovative AI - Artificial Intelligence (AI) and its impact on businesses.
AIOps: The Digital Revolution in IT Operations
This week in Innovative AI
Innovative AI Shorts:
Amazon Invests in Anthropic, OpenAI Rival, to Strengthen Position in AI Market
Findings Show Human Creativity Prevails: Top Performers Outperform Artificial Intelligence in Divergent Thinking Task
OpenAI Unleashes ChatGPT's Multimodal Powers: Now Seeing, Hearing, and Speaking!
Executives’ Highlight: AIOps: The Digital Revolution in IT Operations
Prompts for your Organization: Midjourney to produce ideas for architects; ChatGPT for practicing pitching to a VC
Overview: Center for Deep Tech Innovation Events
+ Registration to our next free webinar on Enterprise AI on 09.10.23Tools to try out: GrammarlyGO
Innovative AI Shorts:
Amazon Invests in Anthropic, OpenAI Rival, to Strengthen Position in AI Market
Amazon has made a strategic investment in Anthropic, a rival to OpenAI. Anthropic, which was co-founded by a former OpenAI researcher, aims to develop a language model similar to OpenAI's GPT while addressing its limitations. This investment comes as Amazon continues to expand its presence in the AI sector and strengthen its capabilities. With this move, Amazon hopes to compete with Microsoft's recent acquisition of OpenAI and establish its footing in the rapidly evolving world of advanced language models.
Findings Show Human Creativity Prevails: Top Performers Outperform Artificial Intelligence in Divergent Thinking Task
A recent study has shown that artificial intelligence (AI) chatbots may possess a level of creativity that rivals that of humans. The study involved comparing the creative abilities of 256 human participants with three current AI chatbots, using a task that measures divergent thinking. The findings revealed that, on average, the AI chatbots performed better than humans by generating more creative and uncommon uses for everyday objects. However, it is important to note that the best human ideas still matched or even exceeded those of the chatbots. While this study highlights the potential of AI in enhancing creativity, it also emphasizes the unique and complex nature of human creativity that may be difficult to fully replicate or surpass with AI technology. These findings raise important questions about the future of creative work in the age of AI and shed light on the relationship between human and machine creativity.
OpenAI Unleashes ChatGPT's Multimodal Powers: Now Seeing, Hearing, and Speaking!
OpenAI has made significant progress on its language model ChatGPT by enhancing its abilities to "see", "hear", and "speak". The upgraded model now uses multimodal capabilities to understand and generate content from both text and images, making it more robust and versatile. By combining text prompts with image inputs, ChatGPT is able to generate more accurate and context-aware responses. OpenAI has also incorporated a new technique named RL training, which helps align ChatGPT's outputs with desired user feedback, enabling continuous improvement. These advancements pave the way for a more interactive and intuitive conversational AI system.
AIOps: The Digital Revolution in IT Operations
In the ever-evolving IT landscape, the sheer volume of data generated can be overwhelming. Traditional IT workflows that rely on manual processes and human intervention often cannot keep up with the pace and complexity of modern digital environments. This is where AIOps promise a new approach to solving this problem. AIOps promise to create smarter, more efficient, and more proactive IT ecosystems by combining artificial intelligence (AI) and IT operations.
At its core, AIOps are more accurately called artificial intelligence for IT operations a way to provide IT systems with brain-like functionality. This enables AIOps to sift through data, make decisions and even predict future challenges.
You can also find a good explanation of AIOps in the following video from IBM:
So how do AIOps achieve their predictive power? To answer this question we would like to provide you with one example of how AIOps operate, found in Vijay Kanade article “What Is Artificial Intelligence for IT Operations (AIOps)? Meaning, Tools, and Use Cases”.
Accordingly, AIOps platforms, e.g., initiate their process by:
(1) Data Collection: AIOps platforms gather data from various sources within an IT environment, including logs from applications and systems, metrics from monitoring tools, and user interaction data.
(2) Data Aggregation and Correlation: The collected data is then aggregated and correlated to provide a unified view of the IT environment, combining both structured and unstructured data.
(3) Pattern Recognition and Anomaly Detection: Machine learning algorithms are applied to analyze the data, establishing baseline performance metrics and detecting anomalies.
(4) Root Cause Analysis: AIOps platforms can determine the underlying causes of incidents by correlating events and metrics.
(5) Predictive Analytics: By utilizing historical data, AIOps can predict future incidents or performance trends.
(6) Automation and Remediation: Routine tasks are automated, and incident resolution is assisted, either by triggering automated responses or providing recommendations to IT teams.
This being said the use cases for AIOps are diverse, hence the way they operate may also vary.
Typical use cases for AIOps include optimizing network performance, managing cloud resources, improving IT service desks through automation, monitoring application performance, and more. Additionally, we believe that AIOps (will) play a central role in cybersecurity by detecting threats, monitoring data center health, helping with capacity planning, streamlining DevOps processes, ensuring optimal digital user experiences, and automating routine IT infrastructure tasks. Furthermore, we see another use case in the financial and healthcare sectors, where AIOps can help secure digital services and provide early detection and warning of anomalies.
The AIOps market
The AIOps market is undergoing rapid change and growth. According to a market research report by Sheer Analytics and Insights, the global AIOps platform market was valued at $3.2 billion in 2020 and is expected to reach an impressive $23.3 billion by 2031. This growth is driven by the increasing complexity of IT environments, with the advent of cloud computing, IoT devices, and growing reliance on digital services. Traditional IT management methods are becoming obsolete, and AIOps platforms provide a comprehensive view of the IT ecosystem, ensuring timely identification and resolution of issues.
The competitive landscape in the AIOps market is therefore very dynamic. Notable players in the market include IBM, Splunk, ServiceNow, AppDynamics, BMC Software, Inc, Broadcom, HCL Technologies Limited, Micro Focus, Moogsoft, ProphetStor Data Services, Inc, Resolve Systems, VMware, Inc, CA Technologies, FixStream, and Correlsense. All of these companies are developing targeted AIOps solutions tailored to meet the diverse needs of the industry, and we expect more innovative features to emerge as the market matures.
The landscape of AIOps
The AIOps landscape is where established tech experts and new innovators come together to shape the future of technology. These platforms use advanced machine learning, not just to add another tool to the IT toolbox, but to help businesses act before problems arise, rather than just reacting to them. Beyond the tech side of things, what's really special about these platforms is how they fit smoothly into current IT systems, giving a clear view of everything from day-to-day monitoring to advanced automation. While AIOps is a big change that has made some companies skeptical about the amount of trust one should have in these upcoming technologies, history showed us that embracing new ways of doing things is often key to long-term success. Therefore, we consider it important to take a closer look at the products on the market.
Therefore, we choose to provide some examples of current AIOps tools here:
IBM Watson AIOps uses natural language processing to interpret unstructured data, enabling the analysis of textual information like incident descriptions. It provides automated root cause analysis by leveraging AI and machine learning, correlating data from various sources to quickly identify the underlying causes of IT issues.
Moogsoft utilizes machine learning and advanced correlation techniques to detect potential incidents early, ensuring system uptime. By leveraging AI and ML, it identifies patterns to prevent recurring issues. The platform also automates workflows for efficient incident routing, remediation, and closure, emphasizing its expertise in service assurance, especially in cloud environments with microservice and ephemeral architectures. This approach empowers organizations to resolve issues confidently, save time, and drive innovation.
Dynatrace: offers unified observability and security through advanced analytics and automation. It uses machine learning to proactively detect incidents, ensuring system uptime. The platform provides insights across infrastructure, applications, and user experiences, and its AI-driven capabilities help businesses swiftly identify and resolve issues, optimizing both performance and security in cloud-native environments
In our view, AIOps is a game-changer for the tech world. It has the power to make IT operations smarter and more efficient. However, because it's a complex technology, it might take some time for many businesses to fully adopt and use it. While we're excited about its potential, we understand that good things often take time to develop and be widely accepted.
Prompts for your Organization
Midjourney to produce ideas for architects
“Create a modern, eco-friendly high-rise design apartment building featuring elements like green roofs, solar panels, natural ventilation systems, and water-saving systems.“
ChatGPT for practicing pitching to a VC
“write e a short pitch text of a company offering a smartphone game like Pokemon Go “; ”Pretend to be a VC that has just read the above pitch for MytsQuest. Ask me questions on it, one at a time.”
Overview: Center for Deep Tech Innovation Events
As some of our readers might know, we offer a series of webinars on the topic of AI (and other technologies in the near future).
Below you find a list of upcoming webinars:
Wednesday, October 4, 2023, 4:00 p.m. (CET) - Prompt Engineering for Business Transformation: A Workshop
Register now here
Wednesday, October 11, 2023, 4:00 p.m. (CET) - free webinar on Enterprise AI
Register now here
For more content, feel free to visit our YouTube channel and LinkedIn
Tools to try out: GrammarlyGO
GrammarlyGO, introduced by Grammarly, is an on-demand generative AI tool tailored to assist users in composing, rewriting, ideating, and replying to texts. Contextually aware, it ensures content aligns with a user's personal voice, offering features like instant composition from prompts, text rewriting for tone and clarity, personalized voice settings, and context-driven email replies. Integrated seamlessly into Grammarly's suite and popular platforms like Gmail and Microsoft Word, users can easily manage its settings and usage limits from their account. Grammarly further elaborates on this innovation in their article titled "Ushering in a New Era of Communication Assistance With GrammarlyGO" on their blog.
Eventually, we come to the end of this newsletter. Stay tuned for the upcoming editions, where we will keep informing you about the latest developments and applications of AI for business and beyond.
Midjourney to produce ideas for architects
“Create a modern, eco-friendly high-rise design apartment building featuring elements like green roofs, solar panels, natural ventilation systems, and water-saving systems.“
ChatGPT for practicing pitching to a VC
“write e a short pitch text of a company offering a smartphone game like Pokemon Go “;” Pretend to be a VC that has just read the above pitch for MytsQuest. Ask me questions on it, one at a time.”
