Mohamed Elhafiz Ahmed’s Post

IA innovations are moving so fast and mostly of them at their peak for high expectations will reach the Plateau within next 5 years. There is a big hype on how all these technologies will change every industry in the short term and how they will define our society in the long term.

There is definitely a bit of a hype around #genai (and other forms of #artificialintelligence) as shown Gartner recent Hype Cycle. We would add that there is definitely tremendous potential in #ai, but it should be applied wisely and start in a narrowly defined field (#softwaredevelopment in our case). That might produce less headlines, but promises better success. Our platform thinks, acts and codes like an #engineer and cuts development time by at least 80-90%. Get in touch anytime for a chat or for a #softwaredemo. #innovation #novendorlockin #artificialintelligence #nocodelowcode #Java #ReactJS

What to do with all the hype around #AI and especially #genai? Gartner Hype Cycle helps to cut down to all the different flavours of AI. Having been in the eye of the #RPA and #automation storm, I know how hard it could be to find substance in the hype. One way to do this is to focus on a well-defined field and excel in it. Apto.ai does exactly this with its #Java #softwaredevelopment platform enabled by #artificialintelligence

Interesting #hype #cycle for #ai by Gartner, though I agree with #computervision & #data #labelling #annotations, I strongly disagree that #edgeai falls under the less than 2-year plateau category. Exhaustive real-time data for preparing a model comes from edge AI, while most of the other fields depend on historical data. What do you feel?

How to read HypeCycle? Depending on your company industry and innovation appetite- some ideas stated on graph might become closer in time, if you will decide to invest your time in attempt to imagine how it transforms or change things you do now.

I have long been a huge fan of the Gartner Hype Cycle for technology. That being said, I do not agree with this particular HC. Specifically, operational business executives will have the most success when they recognize there are many different types of AI. Generative AI is clearly the technology that is the 'rising tide' lifting all other AI technologies. Generative AI should have its own HC because of where it was, where it is now, and where it can go. An executive able to understand and utilize different types of AI for various operational tasks will have the greatest succcess on their business. https://lnkd.in/dJVV5zcn

Changes occur so fast, speed of change certainly have moved and shortened the timeline of the curve from the #hypecycle perspective. There is a big, big gap on market adoption, do you agree? Consulting companies, startups and internal teams need to catch up and deliver real business outcomes at light speed and on budget.

Innovations on the most recent Gartner Hype Cycle for Artificial Intelligence deserve your attention — many in the next two to five years. See the full Hype Cycle: https://gtnr.it/3UvWXRs Gartner for IT | #GartnerIT #AI #ArtificialIntelligence

Hello AI Enthusiasts! 🤖✨ Have you seen the latest Gartner Hype Cycle for Artificial Intelligence? This insightful report not only reveals the current state of various AI technologies, but also provides a glimpse into their potential future trajectories. 🔎 Innovation trigger: On the starting line, we have promising technologies such as Neuro-Symbolic AI, Multiagent Systems, First-Principles AI and Automatic Systems. These cutting-edge innovations are set to revolutionise AI by combining symbolic reasoning with neural networks and improving autonomous decision-making. Although still in their infancy, they hold immense potential for the future. 📈 The peak of inflated expectations: Currently, technologies such as Generative AI, Foundation Models, Synthetic Data and AI TRiSM are booming. Generative AI, in particular, is transforming content creation by producing realistic images and sophisticated text. However, as with any emerging technology, these innovations will need to prove their practical value in real-world scenarios. 📉 The trough of disillusionment: Some AI technologies, such as Edge AI and Knowledge Graphs, face integration and scalability challenges. While they have the potential to revolutionise industries, they need to demonstrate their value in practical applications to progress through the hype cycle. 💡 The Slope of Enlightenment: As we move forward, Smart Apps, Autonomous Vehicles and Cloud-based AI services are gradually proving their value and finding practical applications in various sectors. These technologies are poised to deliver significant improvements and drive innovation in their respective fields. 🏆 Productivity plateau: Mature technologies such as Computer Vision and Data Labelling have already reached the productivity plateau. They are well established and widely used in many applications, from security systems to autonomous vehicles, providing reliable and impactful solutions. 🔮 What's Next? While the journey is full of ups and downs, the future of AI technology promises continuous innovation and transformation. It's essential that businesses stay informed and strategically invest in AI innovations that align with their goals. 📌 Stay curious, keep innovating, and don't forget to share your thoughts in the comments below! #AI #GartnerHypeCycle #FutureOfAI #Innovation #ArtificialIntelligence

Must be both fun and challenging to pull together this AI hype cycle chart. I can see some of the topics, like generative AI, landing in multiple spots along the x-axis.