The ASX climbed 0.47% or 34.30 points to 7,344.20 today and set a new 20-day high, now sitting 3.68% off its 52-week high.
Gains were stronger in early trading but fell off after 11:00pm, although the index still reached its highest level yet this month.
The sectors were, predictably, mostly up, with particular gains in Materials (+1.48%) and Information Tech (+1.34%) while Energy (-0.33%), Financials (-0.14%), Communication Services (-0.32%) and Utilities (-0.19%) fell.
Commodities followed suit for the most part, with nickel (+3.58%) gaining the most behind palladium (+2.30%) and West Texas Crude (+1.94%) while tin took the biggest hit, shedding 3.61%.
The top-performing stocks were NextDC Limited, up 8.36%, and Champion Iron Limited, up 7.20%.
NextDC, a data centre developer, gained on securing enough customers to increase data centre usage to 46% of capacity, up 43% from last guidance.
Champion Iron, on the other hand, is enjoying a strengthening iron ore price (up 1.25% overnight), driven higher by a tropical cyclone brewing off the Western Australian coast that may impact Port Hedland, the world’s biggest export point for iron ore.
In the news today
TigerGPT offers generative AI tool
Tiger Brokers, the company behind share trading platform Tiger Trade, has revealed its TigerGPT technology, the investment sector’s first AI investment assistant according to the company.
The generative AI technology – which has just entered the user testing or 'Beta testing' phase – aims to offer timely stock and market data and deliver in-depth analyses from various sources in a matter of seconds.
This tool will leverage Tiger Broker’s content library and access to paid sources to offer listed companies' profiles and data, financial knowledge and investor education materials and market and stock insights in a swift and easily digestible manner.
"At Tiger Brokers, our commitment is to constantly facilitate global investing by placing innovations at the centre of every step we take in creating the best possible user experience, boosting our users' overall investing literacy, and bringing more sense to smart investing," said Tiger Brokers founder and CEO Wu Tianhua.
"No more overwhelming mountains of scattered data and information, we believe our TigerGPT feature can bring users a deeply valued fresh breeze, by addressing various queries on investment research, quenching curiosities of specific stocks and industries, and presenting the very piece of information needed in a well-articulated and highly-pertinent manner — all the factors needed before making informed, efficient and smart investments."
The use of generative AI as a sort of 'librarian' of vast stores of information has been gaining swift popularity in recent months, especially in the industrial digitisation sector.
Rather than using generative AI to create content from the entirety of information on the internet – which is often inaccurate, and difficult to fact-check – this new use case places AI as a kind of curator of data, skimming through specified databases to produce quick, accurate answers from a company’s own files.
“These technologies have the capability to transform practically every sector or domain of the economy because they can make existing processes more efficient,” Nell Watson, an entrepreneur and machine intelligence researcher, wrote in Irish Tech News.
Watson’s work primarily focuses on protecting human rights and creating ethical AI. She pioneered Deep Machine Vision through her company QuantaCorp, which enables fast and accurate body measurement from just two photos.
“Those who embrace these technologies and master their deployment can enjoy very strong advantages over competitors,” she said.
“The transformative nature of such AI technologies can be compared to how electricity and motive power changed every sector a century ago, with the creation of power drills and tractors instead of mule-driven ploughs.
“All businesses must now learn to recognise the advantages that AI is bringing and will continue to bring to their sector.
“Deep Learning has emerged in the past 10 years or so, enabling amazing new predictive processes that can find patterns with patterns, and make order out of chaos.
“The latest models are even generating computer code, video, 3D models, virtual personalities and music on demand from nothing more than a description of the desired output.
“One might think that ML [Machine Learning] skills will be less needed as a result.
“However, by making the power of state-of-the-art ML clear to the public, the desire for improved machine learning capabilities to optimise almost any problem will be greatly increased.
“Machine learning is here to stay.”
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