MIT Researchers Build New AI Model To Predict Viral Escape

Since time immemorial, viruses have been the chief nemesis of homosapiens. The micro-menace mutates fast rendering vaccines impotent. The phenomenon is called ‘viral escape’.
Massachusetts Institute of Technology (MIT)

Read more: https://analyticsindiamag.com/mit-researchers-build-new-ai-model-to-predict-viral-escape/

#research #virus #vaccine #covid19 #healthtech #artificial-intelligence

What is GEEK

Buddha Community

MIT Researchers Build New AI Model To Predict Viral Escape

MIT Researchers Build New AI Model To Predict Viral Escape

Since time immemorial, viruses have been the chief nemesis of homosapiens. The micro-menace mutates fast rendering vaccines impotent. The phenomenon is called ‘viral escape’.
Massachusetts Institute of Technology (MIT)

Read more: https://analyticsindiamag.com/mit-researchers-build-new-ai-model-to-predict-viral-escape/

#research #virus #vaccine #covid19 #healthtech #artificial-intelligence

Ian  Robinson

Ian Robinson

1623223443

Predictive Modeling in Data Science

Predictive modeling is an integral tool used in the data science world — learn the five primary predictive models and how to use them properly.

Predictive modeling in data science is used to answer the question “What is going to happen in the future, based on known past behaviors?” Modeling is an essential part of data science, and it is mainly divided into predictive and preventive modeling. Predictive modeling, also known as predictive analytics, is the process of using data and statistical algorithms to predict outcomes with data models. Anything from sports outcomes, television ratings to technological advances, and corporate economies can be predicted using these models.

Top 5 Predictive Models

  1. Classification Model: It is the simplest of all predictive analytics models. It puts data in categories based on its historical data. Classification models are best to answer “yes or no” types of questions.
  2. Clustering Model: This model groups data points into separate groups, based on similar behavior.
  3. **Forecast Model: **One of the most widely used predictive analytics models. It deals with metric value prediction, and this model can be applied wherever historical numerical data is available.
  4. Outliers Model: This model, as the name suggests, is oriented around exceptional data entries within a dataset. It can identify exceptional figures either by themselves or in concurrence with other numbers and categories.
  5. Time Series Model: This predictive model consists of a series of data points captured, using time as the input limit. It uses the data from previous years to develop a numerical metric and predicts the next three to six weeks of data using that metric.

#big data #data science #predictive analytics #predictive analysis #predictive modeling #predictive models

Aileen  Jacobs

Aileen Jacobs

1597245602

Researchers Claim Inconsistent Model Performance In Most ML Research

The process of benchmarking is considered to be one of the most crucial assets for the progress of AI and machine learning research. The benchmark datasets are usually fixed sets of data, which are manually, semi-automatically as well as automatically generated to form a representative sample for these specific tasks to be solved by a model.

Recently, researchers from the Institute for Artificial Intelligence and Decision Support, Vienna claimed that the considerable part of metrics currently used to evaluate classification AI benchmark tasks might be inconsistent. It may result in a poor reflection in the performance of a classifier, especially when used with imbalanced datasets.

For the research, they analysed the present aspect of performance metrics that are based on data covering more than 3500 ML model performance results from a web-based open platform.

#developers corner #ai research benchmark #ai research papers #benchmark #benchmarking ai #bias in ml research #inconsistent benchmark

Otho  Hagenes

Otho Hagenes

1619511840

Making Sales More Efficient: Lead Qualification Using AI

If you were to ask any organization today, you would learn that they are all becoming reliant on Artificial Intelligence Solutions and using AI to digitally transform in order to bring their organizations into the new age. AI is no longer a new concept, instead, with the technological advancements that are being made in the realm of AI, it has become a much-needed business facet.

AI has become easier to use and implement than ever before, and every business is applying AI solutions to their processes. Organizations have begun to base their digital transformation strategies around AI and the way in which they conduct their business. One of these business processes that AI has helped transform is lead qualifications.

#ai-solutions-development #artificial-intelligence #future-of-artificial-intellige #ai #ai-applications #ai-trends #future-of-ai #ai-revolution

Shradha Singh

1609159431

AI Models Are Making the World a Better Place

Artificial Intelligence (AI) is not a future trend; it is very much a part of our present and is steering our everyday lives. From the posts we see on our social media profiles to the movies we are recommended by Netflix and products Amazon suggests to us, we actively use AI technology.

Further on, with big companies and makers like NVIDIA, Intel, Qualcomm, and others, innovating the underlying technology (semiconductors), AI models are becoming smarter and better. Here we explore a few ways in which AI is changing our world and making it more advanced and simpler.

AI and the Human World: 4 Big Futuristic Changes
AI Will Improve Remote Learning

Distance learning has existed for many years. But its sudden introduction came as a shocker to the parents as well as teachers as it forced them to learn to teach and learn through the screen.

Artificial Intelligence professionals can help education leaders reduce costs and make education more effective by delivering successful online lessons. It will allow teachers to delegate mundane tasks and take up creative assessments. Planning, assessment, scheduling, and even teaching of facts can be taken care of by the AI.

The tech will allow teachers to focus on building students’ curiosity levels, critical thinking abilities, and creativity. China is leading the way in this with AI solutions in e-Learning with its 9 EdTech unicorns.

It can deliver a learning experience that is customized to a child’s needs.

**AI Will Introduce Physical Interfaces Between Humans and Machines **
Platforms and machines today are better at interacting with us due to AI. However, it is yet to go beyond the software styled interface. In the years to come, AI will go beyond real-world interfaces through which we will talk and interact with AI machines.

Autonomous vehicles are one such example.

Currently, such automation can only be seen in closed doors of factories and warehouses. Plus, these machines are narrow in their activities and rigid. AI-driven automated interfaces and machines will be more sensitive to our needs and intelligence. Artificial Intelligence professionals working in this arena will be high in-demand in future economies.

Latest developments in machine learning and AI models can successfully beat humans through reinforcement learning in games such as Go and DOTA, where an infinite amount of data is generated. This raises hopes for intelligent real-world AI becoming a reality provided enough data and simulations are provided.

#ai models #machine learning #ai #ai machines #ai solutions #futuristic