Below are a few examples of how AI and IoT can be strongly synergistic in improving outcomes across areas such as power, health care, system design, and security. A built-in AI could alert the utility staff to an impending brownout that requires human action to avert. Or the AI could be more sophisticated and proactively turn thermostats up three degrees at homes and non-essential businesses, while keeping the thermostats stable at temperature-sensitive facilities such as hospitals and refrigerated warehouses. The IoT includes everything from very basic sensors to sophisticated devices that have basic intelligence programmed in.
A session on Tuesday featured Christina Qi, the co-founder of a high-frequency trading firm called Domeyard LP; Jonathan Larkin, an executive from Quantopian, a hedge fund taking a data-driven systematic approach; and Andy Weissman of Union Square Ventures, a venture capital firm that has invested in an autonomous hedge fund. Many of the world's largest hedge funds already rely on powerful computing infrastructure and quantitative methods--whether that's high-frequency trading, incorporating machine learning, or applying data science--to make trades. Some have begun to incorporate machine learning into their systems, hand over key management decisions to troves of data scientists, and even crowdsource investment strategies. Domeyard can't incorporate machine learning, Qi says, because machine learning programs are generally optimized for throughput, rather than latency.
Marketing, like most other fields, will feel AI's impact in several areas, including database marketing techniques, search queries and search engine optimization (SEO), personalization, predictive customer service, sales forecasting, customer segmentation, pricing, and many others. Question: Will Artificial Intelligence (AI) be marketing's friend or foe? As AI learns and develops, I can foresee buying behaviors and automated nurture- or real time- programs tied together as an example. Software programs, created and managed by humans, perform predefined micro-tasks following pre-set decision trees designed to automate routine, repeatable tasks.
Data from BrightEdge, an enterprise search engine optimization (SEO) and content performance marketing company, and SurveyMonkey looked at the probability that US market leaders will use AI or deep learning to develop their 2017 content marketing efforts. While a large share of respondents (57.1%) said they're unlikely to use AI or deep learning in their content marketing, a significant number felt differently. For example, nearly a third (31.4%) of respondents said they were somewhat likely to use AI to help flesh out their content marketing strategy. Meanwhile, 2.8% said they're already using AI to develop their content efforts.
With the right conditions in place, businesses can develop what new Accenture research identifies as AIQ--Artificial Intelligence Quotient--a measure of a company's ability to strike the necessary balance of in-house AI innovation and external collaboration with entrepreneurial partners. Companies that have optimized AI strategies in this way are already generating greater shareholder value through a winning combination of technology, data science and people. This allows innovation to create and scale artificial intelligence solutions specific to multiple industry sectors. Greater internal investment might be best focused on proprietary technologies that create new products and services.
Today, at asset management companies and other financial institutions, there are still large teams of analysts and portfolio managers, sifting through data, developing investment theses and making asset allocation decisions. Let's assume that you use very sophisticated AI-driven models to scan data from not just the market but a whole plethora of other sources to define, implement, monitor, refine and adjust your trading strategies. The kinds of people employed in the industry will change; we will need people who can model data, and others who can validate the models and the results. One hedge fund taking artificial intelligence to the next level is Numerai - which doesn't even employ the AI talent!
In addition to content creation, AI allows marketers to target content promotion. In the future, this information will be used to personalize website algorithms and automated email content, formulating articles relevant to the customer based on data. Rather than requiring the sales team to call all leads, propensity models generated by machine learning can be trained to score leads, allowing the sales team to establish how likely a lead is to buy. Dynamic price optimization through machine learning can help boost sales by correlating pricing trends with sales trends by using an algorithm, which will only offer promotions to those needed to convert.
Hackers are increasingly using this technique, known as steganography, to trick internet users and smuggle malicious payloads past security scanners and firewalls. That doesn't mean people can't discover attacks that use steganographic techniques and learn from how they work. What's clear is that instead of being reserved for the most sophisticated hacks, steganography now crops up in malvertising, phishing, run-of-the-mill malware distribution, and exploit kits (like a tool called Sundown that is popular with hackers looking to exploit software vulnerabilities). "Steganography in cyber attacks is easy to implement and enormously tough to detect, so cyber criminals are shifting towards this technique."
DALIAN, China--(BUSINESS WIRE)--New research from Accenture (NYSE:ACN) reveals that artificial intelligence (AI) could accelerate China's economic growth rate from 6.3 percent to 7.9 percent by 2035, by transforming the nature of work and opening new sources of value and growth. As a new factor of production, Accenture finds that AI is poised to boost China's gross value added (GVA) by USD $7,111 billion by 2035. The report also finds that AI has the potential to boost China's labor productivity by 27 percent by 2035 - driven by innovative AI technologies that enable people to make more efficient use of their time. Accenture's findings also reveal that Manufacturing, Agriculture, Forestry and Fishing, and Wholesale and Retail are the three industry sectors that will benefit most from the application of AI in China, with boosts in their annual GVA growth rates by 2 percentage points, 1.8 percentage points and 1.7 percentage points respectively by 2035.
New research from Accenture (NYSE:ACN) reveals that artificial intelligence (AI) could accelerate China's economic growth rate from 6.3 percent to 7.9 percent by 2035, by transforming the nature of work and opening new sources of value and growth. AI is poised to boost China's GVA by USD $7,111 billion by 2035 (Graphic: Business Wire) The report, titled "How Artificial Intelligence Can Drive China's Growth," explores new insights into AI and its impact on China's economy. As a new factor of production, Accenture finds that AI is poised to boost China's gross value added (GVA) by USD $7,111 billion by 2035. Accenture's findings also reveal that Manufacturing, Agriculture, Forestry and Fishing, and Wholesale and Retail are the three industry sectors that will benefit most from the application of AI in China, with boosts in their annual GVA growth rates by 2 percentage points, 1.8 percentage points and 1.7 percentage points respectively by 2035.