Verdict lists five of the most popular tweets on artificial intelligence (AI) in Q2 2021 based on data from GlobalData’s Influencer Platform.
The top tweets were chosen from influencers as tracked by GlobalData’s Influencer Platform, which is based on a scientific process that works on pre-defined parameters. Influencers are selected after a deep analysis of the influencer’s relevance, network strength, engagement, and leading discussions on new and emerging trends.
The most popular tweets on AI in Q2 2021: Top five
1. Vala Afshar’s tweet on an AI-powered robot that can pick fruits
Vala Afshar, chief digital evangelist at Salesforce, a cloud-based customer relationship management (CRM) platform provider, shared a video on an AI-powered flying robot that can pick fruits. The robot was developed by an Israeli start-up Tevel and is being tested on large farms in Spain, Italy, and the US.
The robot is capable of identifying different types of fruits. It uses AI to check for ripeness of the fruits and then picks them, while setting aside damaged fruits. It can perform other functions such as packing the fruits, providing update in real time to a central computer about the volume of fruits it has picked, and pruning the orchards after harvest.
The robot can also help in addressing the challenges faced by farmers in picking the fruit produce, as well as labour shortage. It, thus, reduces the labour, packing, and shipping costs involved in the production of fruits.
The future of fruit picking is done with AI powered drones https://t.co/y016zh7EKC pic.twitter.com/Zq6EKMbCVa
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By GlobalData— Vala Afshar (@ValaAfshar) April 5, 2021
Username: Vala Afshar
Twitter handle: @ValaAfshar
Retweets: 233
Likes: 697
2. Kirk Borne’s tweet on the impact of emerging technologies on industries
Kirk Borne, chief science officer at DataPrime, a provider of data science, AI and machine learning products and services, shared an article on how emerging technologies such as AI, Internet of Things (IoT) and blockchain are impacting industries. AI, for example, has an impact on various industries including education, healthcare, defence, agriculture, and finance. AI supported machine learning and deep learning can help businesses in performing property evaluations in the real estate industry. It can also empower online tutoring systems in the education sector to collect data and help learners gain knowledge.
Furthermore, AI technology can be used to analyse patients’ data in clinical notes and reports in the healthcare sector. Technology company IBM, for example, is using its IBM Watson suite of AI applications to build cognitive applications that can help in finding potential treatment options for patients by analysing data in clinical notes.
How #EmergingTechnologies are impacting industries: https://t.co/NAfHYRnIeI
———————#BigData #DataScience #AI #MachineLearning #Automation #IoT #IIoT #IoTPL #IoTCommunity #Blockchain #DigitalTransformation #fintech #insurtech #HealthTech #Retail #EdTech #Industry40 #4IR #AR #VR pic.twitter.com/5aB3NHJWhz— Kirk Borne (@KirkDBorne) May 8, 2021
Username: Kirk Borne
Twitter handle: @KirkDBorne
Retweets: 99
Likes: 185
3. Ronald van Loon’s tweet on the Intel Xeon processor family with built-in AI hardware
Ronald van Loon, CEO and principal analyst at Intelligent World, an influencer network that connects businesses and influencers to new audiences, shared a video on how businesses can incorporate AI into their operations. He noted that businesses and organisations need to leverage AI to capitalise on the emerging business opportunities and innovate within their sectors.
Van Loon shared a presentation from Wei Li, vice president and general manager of machine learning performance at Intel, on the third generation of Intel Xeon scalable processor family that has built-in AI hardware. The processor can help organisations to leverage AI capabilities and enables optimisation of end-to-end data science software. Intel also introduced the Intel® Optane™ Persistent Memory designed especially for terabyte-scale data science.
Opportunities, #Innovations & Capabilities of #AI Everywhere
by @Ronald_vanLoon & Wei Li |#IntelPartner @Intel #XeonScalable #IoT #Network #Security #DeepLearning #MachineLearningCc: @iamBrianGraham @antgrasso_IT pic.twitter.com/2eEKxif1s8
— Ronald van Loon (@Ronald_vanLoon) June 25, 2021
Username: Ronald van Loon
Twitter handle: @Ronald_vanLoon
Retweets: 108
Likes: 32
4. Giuliano Liguori’s tweet on keeping AI ethical
Giuliano Liguori, founder of Digital Leaders, a provider of digital transformation and innovation management services, shared an article on keeping AI ethical. AI can enhance finance and other business operations within an organisation, while providing a competitive advantage. Finance professionals, however, need to understand and manage the risks that emerge with respect to compliance and brand reputation while using AI.
The data being used by the AI model is continuously changing due to the changes in consumer behaviour or business operations. The changes lead to unintentional bias and cause deviations in the performance of the AI model, which can create problems for organisations in terms of risk and compliance.
The difficulty in managing risk and compliance has, therefore, been cited as the main barrier to the adoption of AI by 80% of enterprises in 2021. The article proposes a comprehensive strategy encompassing AI policy, governance, AI model monitoring, and co-ordinated remediation to keep AI impartial and ethical.
How to Keep Your #AI Ethical by @ModelOp_Co https://t.co/Lm9X5DCxPs Via @ingliguori #modelops #mlops #machinelearning #DataScience #digitaltransformation #CIOs #innovation #finance #fintech #datascientist #DEVCommunity #100DaysOfCode #ArtificialIntelligence @antgrasso @mvollmer1 pic.twitter.com/9B6pYtJsfz
— Giuliano Liguori (@ingliguori) June 4, 2021
Username: Giuliano Liguori
Twitter handle: @ingliguori
Retweets: 100
Likes: 56
5. Spiros Margaris’ tweet on the future of artificial neural networks
Spiros Margaris, a venture capitalist and founder of Margaris Ventures, a venture capital firm, shared an article on the future of artificial neural networks. Neural networks combined with other cutting-edge technologies such as AI, machine learning, and big data have unlocked multiple applications in industries.
Chatbots in the retail sector, for example, help automate customer support activities and provide a user-friendly experience. Similarly, neural networks can be used to evaluate and forecast natural disasters such as earthquakes, floods, and volcanic eruptions by analysing seismographs and air pressure data. Organisations need to invest in artificial neural networks to unlock opportunities and develop effective business strategies, the article adds.
Artificial Intelligence:
The Evolution of #NeuralNetworkshttps://t.co/xnzBXuN8Cz #fintech #AI #ArtificialIntelligence #MachineLearning #DeepLearning @joshinav @BBNTimes_en @ipfconline1 @Julez_Norton @kalydeoo @asokan_telecom @WSWMUC @mvollmer1 @enilev @jblefevre60 @Fisher85M pic.twitter.com/a9iYEHkW56
— Spiros Margaris (@SpirosMargaris) June 5, 2021
Username: Spiros Margaris
Twitter handle: @SpirosMargaris
Retweets: 81
Likes: 78
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