Conquering AI horizons is now even harder than it was in the very beginning, when artificial intelligence was considered a science fiction. Sophisticated, AI-driven solutions are permeating nearly every aspect of our lives like Data Labeling. More AI, though, requires more data that underpins these tech solutions. Say you are working on the new project -- a face recognition system for a large enterprise. First, you need to train the model to recognize human faces by feeding it with a decent amount of labeled training data. Now the question is, where to find the most perfectly annotated datasets?

With a variety of businesses integrating AI technology and machine learning models into their business practices, AI has become less of a novelty and more mainstream over the past few years. With ever-growing amounts of data generated worldwide, you are likely already in possession of the data you need for your machine learning models and industry-specific use case. Cogito is one of the top data annotation companies with its wide array of data annotation and labeling services. As an industry leader in the AI and machine learning space and a premier AI training data procurer, it can be your true ally in integrating automation into your business processes. Getting us on board for annotating and labeling the raw & unstructured datasets and validating the training data can get you sorted for the automation goals.

Whenever we talk about Artificial Intelligence (AI) and Machine Learning (ML), what we instantly imagine are powerful tech companies, convenient and futuristic solutions, fancy self-driving cars, and basically everything that is aesthetically, creatively, and intellectually pleasing. What hardly gets projected to people is the real world behind all the conveniences and lifestyle experiences offered by AI. For your device to set an alarm clock just by listening to your voice, hundreds of hours of work would have gone through at the back end -- right from the time of ideation to developing prototypes and testing. Now, imagine the scale of operations and efforts behind your Netflix recommendation engines, eCommerce personalizations, home automation systems, on-demand transport, and food delivery solutions, and basically anything powered by a smartphone or an app. Today's spectrum of artificial intelligence is just like a fancy restaurant that gets marketed among people.

Whenever we talk about Artificial Intelligence (AI) and Machine Learning (ML), what we instantly imagine are powerful tech companies, convenient and futuristic solutions, fancy self-driving cars, and basically everything that is aesthetically, creatively, and intellectually pleasing. What hardly gets projected to people is the real world behind all the conveniences and lifestyle experiences offered by AI. For your device to set an alarm clock just by listening to your voice, hundreds of hours of work would have gone through at the back end - right from the time of ideation to developing prototypes and testing. Now, imagine the scale of operations and efforts behind your Netflix recommendation engines, eCommerce personalizations, home automation systems, on-demand transport, and food delivery solutions, and basically anything powered by a smartphone or an app. Today's spectrum of artificial intelligence is just like a fancy restaurant that gets marketed among people.

At Aptiv, we believe that our mobility solutions have the power to change the world. Our Autonomous Mobility team is focused on developing and commercializing self-driving cars and systems that enable point-to-point mobility in challenging urban driving environments. With talented teams working across the globe in Boston, Pittsburgh, Las Vegas, Santa Monica, and Singapore, Aptiv is the first company to deploy commercial robotaxis to the public. Today, Aptiv has provided over 80,000 autonomous rides to members of the public passengers in Las Vegas -- the world's largest public deployment of self-driving vehicles. In September 2019, Aptiv announced a 50/50 joint venture with Hyundai Motor Group, bringing together HMG and Aptiv's advanced engineering and R&D capabilities, our global footprint, and shared commitment to advancing autonomous driving technology.

If you've ever built a machine learning algorithm, you'll know that gathering labeled datasets is a tremendous undertaking. Trying to conduct data annotation in-house only distracts teams from what they do best: building a strong AI. Outsourcing data annotation services is a proven way for teams to boost productivity, decrease development time and stay ahead of the competition. Individuals, researchers, companies, and governments are increasingly turning to data annotation companies as a viable solution to obtain both crowdsourced annotators and off-the-shelf annotation tools. As the number of AI training data service providers grows, how do you decide which to trust?