In 2018, Medium.com highlighted eight key trends that would shape the future of artificial intelligence. Big data analytics is not just a passing trend—it's an ongoing evolution. As data volumes continue to grow, so does the sophistication of analytics. Predictive analytics, in particular, is still in its early stages, and we've only scratched the surface of its potential. By leveraging current data mining, machine learning, and AI techniques, businesses have already started using these tools to forecast sales, optimize marketing strategies, and improve decision-making. These technologies are interconnected and are gradually reshaping the way we work every day, with more changes on the horizon.
Here are some key statistics from the AI world regarding big data, predictive analytics, and machine learning:
- By 2018, 75% of developers will integrate at least one AI feature into business applications (IDC).
- By 2019, 100% of IoT activities will rely on AI functions (IDC).
- By 2020, 30% of companies will use AI to enhance at least one core process (Gartner).
- By 2020, algorithms will influence hundreds of millions of global behaviors (Gartner).
- By 2020, the AI market will surpass $40 billion (Constellation Research).
- By 2025, AI will drive 95% of user interactions (Servion).
**Trend 1 – Big Companies Will Lead the Way**
Amazon, Google, Facebook, and IBM are expected to dominate AI development. These giants have the resources to collect massive amounts of data, which is essential for training effective AI models. Here’s a closer look at their AI initiatives:
- **Amazon**: Has been investing in AI for over 20 years. It crawls data from 5 billion web pages, processes over 500,000 JPEG images, and monitors 250 million news items daily. Its Echo device leads the voice assistant market by over 70%.
- **Google**: Maintains one of the largest dataset libraries, with 10–15 exabytes of data. It has a team of 1,300 researchers at Google Brain and uses TensorFlow, an open-source ML platform. Google Earth contains 3 petabytes of data, and Street View holds about 20 petabytes of images.
- **Facebook**: Processes 2.5 billion pieces of content daily, with 500 terabytes of data. It has 80 researchers at FAIR and translates 2 billion posts across 40 languages daily.
- **IBM**: Invested $240 million over 10 years to create the MIT-IBM Watson AI Lab. The Watson Group has over 7,000 applications built through its ecosystem.
**Trend 2 – Integration of Algorithms and Technologies**
Smaller players like Intel, Salesforce, and Twitter will follow the lead of big tech firms by integrating AI into their platforms. Data sharing and algorithm consolidation will make AI more efficient. For example, Google acquired DeepMind to develop a universal learning algorithm, while Facebook bought Wit.AI for speech recognition and Ozlo for virtual assistants.
**Trend 3 – Crowdsourcing Data Will Grow**
AI companies will increasingly rely on crowdsourced data to train their models. Platforms like Google and Amazon use crowdsourcing to improve image recognition, translation, and voice assistants. As Joel Gurin noted, people are becoming more comfortable sharing knowledge through social media, making this approach even more powerful.
**Trend 4 – M&A Activity Will Increase**
Mergers and acquisitions will become more common as companies compete for talent and data. Small AI startups will be acquired by larger firms, as data and algorithms are both critical to success. As Hod Lipson said, “Data is fuel and algorithms are engines.â€
**Trend 5 – AI Tools Will Become More Accessible**
Big tech companies will open up their AI tools to increase market share. Frameworks, APIs, and SDKs will become standard, allowing smaller companies to access advanced AI capabilities. This democratization will foster innovation and new applications.
**Trend 6 – Human-Computer Interaction Will Improve**
Tools like Siri and Alexa are just the beginning. Future AI systems will recognize emotions, understand context, and interact more naturally. Manufacturing and non-consumer solutions will also see significant improvements in 2018.
**Trend 7 – AI Will Impact More Industries**
From healthcare to finance, AI is already transforming multiple sectors. In 2018, it will expand further, enabling faster legal document analysis, smarter education tools, and better patient care through predictive analytics.
**Trend 8 – Security, Privacy, and Ethics Will Be Critical**
As AI becomes more embedded in daily life, concerns around security, privacy, and ethics will rise. Issues like data breaches, biased algorithms, and autonomous weapons will need urgent attention. 2018 will mark a turning point in how society addresses these challenges.
**Conclusion**
Although AI has been around for decades, the version we know today is still in its early stages. While there is a lot of excitement around AI applications—from self-driving cars to virtual assistants—most of them are still in the process of being refined and deployed. Despite the hype, AI has a long way to go. 2018 was a pivotal year, and we can expect even more progress in the years to come.
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