How Retailers Can Overcome Issues with Optical Character Recognition (OCR)

How Retailers Can Overcome Issues with Optical Character Recognition (OCR)

Automated solutions like OCR can help tackle retail data transcription at scale, but maintaining data quality remains a major challenge.

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How Retailers Can Keep Up with Post-Pandemic Data Demands

How Retailers Can Keep Up with Post-Pandemic Data Demands

Retail data transcription is time-consuming and tedious work, not to mention notoriously hard to scale. Here’s how retailers can overcome those challenges.

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Does Not Compute: The NLP Context Conundrum

Does Not Compute: The NLP Context Conundrum

The nuances of language can be difficult for a machine to understand, hence the need for human input to accelerate testing and ensure quality control.

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Sentiment Analysis—and Why Computers Can't Do it Alone

Sentiment Analysis—and Why Computers Can't Do it Alone

Sentiment analysis can turn the abundance of online information into actionable insights, but machines can’t do everything by themselves.

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4 Reasons Financial Firms Should Outsource Document Transcription

4 Reasons Financial Firms Should Outsource Document Transcription

In a data-heavy sector like finance, scaling routine operations like document transcription can be difficult, but outsourcing can help in a variety of ways

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How Fintech Companies Securely Outsource Data Processing

How Fintech Companies Securely Outsource Data Processing

Fintech firms are understandably wary of outsourcing data processing, but security measures exist to mitigate risk and maximize workflow efficiency.

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ICYMI: Key Insights from Smart Cities Expert Jonathan Reichental

ICYMI: Key Insights from Smart Cities Expert Jonathan Reichental

In our latest event, we talked with smart cities expert Jonathan Reichental about the future of urban development. Here are some key insights from our chat

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4 NLP Innovators You Should Know About

4 NLP Innovators You Should Know About

With almost half of all online search queries now being spoken, natural language processing (NLP) is booming. Learn about 4 top innovators in the space.

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ICYMI: Key Insights from Data Science Icon Usama Fayyad

ICYMI: Key Insights from Data Science Icon Usama Fayyad

3 key takeaways from our latest LinkedIn Live event where we explored the state of AI & the importance of integrating human intervention with automation.

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Now is the Time for Medical AI Adoption

Now is the Time for Medical AI Adoption

Healthcare providers face mounting pressure to increase clinical efficiency and improve patient outcomes. The need for automation and AI is now.

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How Natural Language Processing (NLP) is Revolutionizing Financial Services

How Natural Language Processing (NLP) is Revolutionizing Financial Services

From spotting trends in financial markets to empowering better client experiences, natural language processing (NLP) is transforming the finance sector.

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ICYMI: Key Insights from HITL Expert Robert Monarch

ICYMI: Key Insights from HITL Expert Robert Monarch

Learn 3 key takeaways from our latest LinkedIn Live event where we explored what it takes to combine human and machine intelligence effectively.

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4 Data Hurdles in Medical AI Development

4 Data Hurdles in Medical AI Development

The rise of medical AI solutions shows great promise, but there are still important hurdles to overcome, such as concerns about privacy and data accuracy.

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5 Ways Artificial Intelligence Is Transforming Fintech

5 Ways Artificial Intelligence Is Transforming Fintech

From fraud detection to automated loan approvals, AI is transforming the world of fintech with smoother client experiences and reduced financial risk.

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The AI & Automation Must-Have: Humans-in-the-Loop

The AI & Automation Must-Have: Humans-in-the-Loop

Humans are necessary while automating decisions and processes with AI, machine learning, and RPA. Experts discuss the need for humans in the loop (HITL).

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3 Examples: Solving Automation and ML Exceptions with Humans in the Loop

3 Examples: Solving Automation and ML Exceptions with Humans in the Loop

Learn how CloudFactory’s managed workforce worked with 3 companies, each with a problem involving data, automation, and/or ML.

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