Machine Learning/Finance - Revision history

Admin at 22:31, 21 December 2021

2021-12-21T22:31:40Z

Admin at 02:56, 20 July 2021

2021-07-20T02:56:24Z

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 =Research papers=
 ==2021.05.21 Multi-Horizon Forecasting for Limit Order Books: Novel Deep Learning Approaches and Hardware Acceleration using Intelligent Processing Units==
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 =The Press=
 ==2021.07.16 Blender Bot 2.0: An open source chatbot that builds long-term memory and searches the internet==

Admin at 08:13, 19 July 2021

2021-07-19T08:13:46Z

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 =Research papers=
 ==2021.07.16 Blender Bot 2.0: An open source chatbot that builds long-term memory and searches the internet==
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 [...]
 </blockquote>
 ==2021.07.09 China Targets AI Dominance by 2030==

Admin at 08:13, 19 July 2021

2021-07-19T08:13:12Z

← Older revision		Revision as of 08:13, 19 July 2021
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	=Research papers=		=Research papers=

			==2021.07.16 Blender Bot 2.0: An open source chatbot that builds long-term memory and searches the internet==

			'''Jason Weston (Research Scientist), Kurt Shuster (Research Scientist). Facebook AI. July 16, 2021. <span class="plainlinks">https://ai.facebook.com/blog/blender-bot-2-an-open-source-chatbot-that-builds-long-term-memory-and-searches-the-internet/</span>'''

			<blockquote>
			* Facebook AI Research has built and open-sourced BlenderBot 2.0, the first chatbot that can simultaneously build long-term memory it can continually access, search the internet for timely information, and have sophisticated conversations on nearly any topic. It's a significant update to the original BlenderBot, which we open-sourced in 2020 and which broke ground as the first to combine several conversational skills—like personality, empathy, and knowledge—into a single system.
			* When talking to people, BlenderBot 2.0 demonstrated that it's better at conducting longer, more knowledgeable, and factually consistent conversations over multiple sessions than its predecessor, the existing state-of-the-art chatbot.
			* The model takes pertinent information gleaned during conversation and stores it in a long-term memory so it can then leverage this knowledge in ongoing conversations that may continue for days, weeks, or even months. The knowledge is stored separately for each person it speaks with, which ensures that no new information learned on one conversation is used in another.
			* During conversation, the model can generate contextual internet search queries, read the results, and incorporate that information when responding to people's questions and comments. This means the model stays up-to-date in an ever-changing world.
			* Today we're releasing the complete model, code, and evaluation setup, as well as two new conversational data sets—human conversations bolstered by internet searches, and multisession chats with people that reference previous sessions—used to trin the model, so other researchers can reproduce this work and advance conversational AI research.

			[...]
			</blockquote>

	==2021.05.21 Multi-Horizon Forecasting for Limit Order Books: Novel Deep Learning Approaches and Hardware Acceleration using Intelligent Processing Units==		==2021.05.21 Multi-Horizon Forecasting for Limit Order Books: Novel Deep Learning Approaches and Hardware Acceleration using Intelligent Processing Units==

Admin at 09:16, 18 July 2021

2021-07-18T09:16:39Z

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 '''Key points:''' ''Goldman, Mission Holdings and Sallie Mae also backed startup. Palo Alto firm seeks to be profitable in first half of 2023.''
 Deserve, a credit-card technology startup, raised $50 million from backers including Mastercard Inc. and Ally Financial Inc.'s strategic investment arm, its chief executive officer said in an interview.
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 ''(Updates to add details of a partnership in the second paragraph. An earlier story was corrected to remove a reference to a partner company.)''
 ==2021.06.08 Man Group-Oxford Quants Say Their AI Can Predict Stock Moves==

Admin at 09:03, 18 July 2021

2021-07-18T09:03:31Z

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 Jian-Wei Pan at the University of Science and Technology of China in Hefei and his colleagues say their quantum computer has solved a problem in just over an hour that would take the world's most powerful classical supercomputer eight years to crack, and may yet be capable of exponentially higher performance.
 </blockquote>
 ==2021.06.08 Man Group-Oxford Quants Say Their AI Can Predict Stock Moves==

Admin at 16:37, 17 July 2021

2021-07-17T16:37:46Z

← Older revision		Revision as of 16:37, 17 July 2021
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	When it comes to traders' day-to-day life 55 per cent will continue to work from home for average of four days a week.		When it comes to traders' day-to-day life 55 per cent will continue to work from home for average of four days a week.
			</blockquote>

			==2020.12.29 Nvidia rival Graphcore raises $222 million for AI chips with potential IPO on the horizon==

			'''Sam Shead. CNBC. Published Tue, Dec 29 2020, 6:25 AM EST, updated Tue, Dec 29 2020, 6:49 AM EST. <span class="plainlinks">https://www.cnbc.com/2020/12/29/graphcore-raises-222-million-to-take-on-nvidia-with-ai-chips.html</span>'''

			'''Key points:'''

			* Graphcore has raised $222 million as it looks to take on U.S. rivals Nvidia and Intel.
			* The Series E funding round, which comes less than a year after Graphcore raised a $150 million extension to its last round, values the company at $2.77 billion.
			* Total investment in Graphcore now stands at $710 million.

			<blockquote>
			London—U.K.-based chipmaker Graphcore announced Tuesday that it had raised $222 million of investment as it looks to take on U.S. rivals Nvidia and Intel.

			Graphcore said it will use the funding to support its global expansion and to accelerate the development of its intelligence processing units (IPUs), which are specifically designed to power artificial intelligence software. The company has already shipped tens of thousands of its chips to customers including Microsoft and Dell.

			The Series E funding round, which comes less than a year after Graphcore raised a $150 million extension to its last round, values the company at $2.77 billion, up from $1.5 billion in 2018.

			Graphcore CEO and co-founder Nigel Toon told CNBC in July: "We're now at the point where we're not really looking for venture investors in the business. We're more interested in companies that would be long term investors and holders of the stock, perhaps, in the public markets, if we ever reach that point."

			At the time, Toon said going public is "ideally what we would like to do" but he stressed "lots of water still has to flow under the bridge before we get to that point."

			Total investment in Graphcore now stands at $710 million and the four-year-old company has $440 million of cash on hand.

			The latest funding round was led by the Ontario Teachers' Pension Plan Board while other new investors included private equity investor Baillie Gifford, venture capital investor Draper Esprit, as well as funds managed by Fidelity International and Schroders.

			On Tuesday, Toon said in a statement: "Having the backing of such respected institutional investors says something very powerful about how the markets now view Graphcore. The confidence that they have in us comes from the competence we have demonstrated building our products and our business."

			He added: "We have created a technology that dramatically outperforms legacy processors such as GPUs, a powerful set of software tools that are tailored to the needs of AI developers, and a global sales operation that is bringing our products to market."

			'''Serial chip entrepreneurs'''

			Graphcore was founded in June 2016 in Bristol, England, by Toon and Simon Knowles, who sold their previous chip company, Icera, to Nvidia for $435 million in 2011. The pair formed the initial idea for Graphcore in a small pub called the Marlborough Tavern in Bath in January 2012.

			Today, the company employs around 450 people in Bristol, Cambridge, London, Beijing, Oslo, Palo Alto, Seattle, and Hsinchu in Taiwan. It expects the number to grow to 600 by the end of 2021.

			But the rapid growth hasn't come cheap. It made a pre-tax loss of $95.9 million on revenues of $10.1 million in 2019, according to an annual report filed on U.K. business registry Companies House.

			Santa Clara heavyweights Intel and Nvidia are two of the obvious front runners in the AI chip market given their expertise in chip making. The companies haven't disclosed how many of their AI-optimized chips have been sold. However, over a trillion computer chips are expected to be shipped in 2020, according to market data website Statistica. In 2019, Intel's slice of the overall chip market came in at 15.7% and it has been the market leader every year since 2008, with the exception of 2017 when Samsung took the number one spot.

			Graphcore's Toon criticized Nvidia's plan to buy U.K. chip designer Arm from SoftBank for $40 billion, saying it is bad for competition.

			"We believe that Nvidia's proposed acquisition of Arm is anti-competitive," he said. "It risks closing-down or limiting other companies' access to leading edge CPU processor designs which are so important across the technology world, from datacenters, to mobile, to cars and in embedded devices of every kind."

			Google, Amazon and Apple are also working on their own AI chips.

			'''Sequoia backs Nvidia and Graphcore'''

			Previous investors in Graphcore include the likes of Microsoft and BMW iVentures, as well as venture firms like London's Atomico and Silicon Valley's Sequoia, which has also backed Nvidia.

			Last month Sequoia partner Matt Miller told CNBC: Graphcore "are in this position where they always have people coming at them trying to give them more money. So, they do not need funding. They are well funded for the next several years, but they definitely have people trying to invest in the company."

			He added: "I don't think that you have to take on Nvidia because the market is so huge. Taking on Nvidia is like this huge task. It's a huge company with billions of revenue and incredible teams doing all sorts of wonderful things. I think that what Graphcore has the opportunity to do is be a very strong player in the AI microprocessor market. It continues to have great progress with many of the cloud providers, and many people want to be diversified. They don't want to be all in with one chip."

			Graphcore launched its second generation IPU earlier this year despite disruption from the coronavirus pandemic.
	</blockquote>		</blockquote>

Admin at 09:44, 15 July 2021

2021-07-15T09:44:55Z

← Older revision		Revision as of 09:44, 15 July 2021
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	China has set its sights on building a domestic AI industry worth nearly $150 billion in the next few years and of becoming the leading AI power by 2030.		China has set its sights on building a domestic AI industry worth nearly $150 billion in the next few years and of becoming the leading AI power by 2030.
			</blockquote>

			==2021.07.07 U.K. Deploys Fastest Supercomputer to Fight Dementia, MS==

			'''Adeola Eribake. Bloomberg. July 7, 2021, 12:01 AM GMT+1. <span class="plainlinks">https://www.bloomberg.com/news/articles/2021-07-06/nvidia-boots-up-u-k-supercomputer-to-boost-drug-research-nhs</span>'''

			'''Abstract:''' ''Developed in partnership with AstraZeneca, GlaxoSmithKline. Nvidia waiting for approval for its $40 billion takeover of Arm.''

			<blockquote>
			Nvidia Corp. has built a U.K. supercomputer for scientists and drug makers that will allow researchers to model diseases, discover new medicines and advance knowledge of the human genome.

			The Cambridge-1 will be the country's most powerful and one of the top 50 supercomputers worldwide. It was developed in partnership with AstraZeneca Plc and GlaxoSmithKline Plc, Nvidia said in a statement on Wednesday.

			Other founding members include Guy's Hospital and St Thomas' Hospital trust, part of the U.K.'s National Health Service, as well as King's College London.

			"Through this partnership, we will be able to use a scale of computational power that is unprecedented in health-care research," said Sebastien Ourselin, head of the School of Biomedical Engineering & Imaging Sciences at King's College London. "It will be truly transformational for the health and treatment of patients."

			Oxford Nanopore, a DNA sequencing startup that's preparing to debut on the London Stock Exchange will also get access to Cambridge-1, allowing it to improve its artificial intelligence algorithms in hours instead of days, the startup said in the statement.

			Rather than a single unit, the Cambridge-1 is made up of several modules working together. This parallel processing lets the computer carry out tasks simultaneously, allowing for greater speeds. It was also faster to build, coming together in about a quarter of the time it takes to construct similar machines.

			The supercomputer has a computing capability of more than 400 petaflops. That's close to the world's fastest, the Fugaku machine in Japan. Top500, which publishes a twice-yearly list of the fastest supercomputers, included the Cambridge-1 at No. 41 on its most recent ranking, published at the end of June.

			The speed and capabilities that supercomputers offer scientists are crucial as they try to make sense of unprecedented amounts of data. "We accumulated more data in one quarter in 2020 than in the last 300 years," said Kim Branson, GSK's senior vice president and global head of AI-ML.

			The machine, which cost $100 million to build, was announced in October, a month after Nvidia launched a $40 billion bid for semiconductor designer Arm Ltd. Arm's technology is ubiquitous in smartphones and other consumer electronics, making the deal controversial among Nvidia's competitors, who rely on the designs. The U.K. has also expressed concerns that selling Arm, which is currently owned by Softbank Group Corp., has national security implications and the country's competition authority is due to submit a report at the end of the month.

			Nvidia said it's already developing another supercomputer, which is to be made with Arm technology.

			The Cambridge-1 will be kept at a site run by Kao Data Campus just outside London and about 40 miles south of its namesake city.

			King's College and London hospital group Guy's and St Thomas' will use the new AI capability to learn from MRI scans and then generate synthetic brain images, creating models to help scientists better understand diseases such as dementia, stroke, brain cancer and multiple sclerosis. That could allow for earlier diagnosis and treatment, the university and teaching hospital said.

			Nvidia said it would work with its partners to share the insights gained with the wider scientific community. For example, AstraZeneca will open up one of its projects, an AI-based model for chemical structures to help with drug discovery, to other scientists.

			"Cambridge-1 will empower world-leading researchers in business and academia with the ability to perform their life's work on the U.K.'s most powerful supercomputer, unlocking clues to disease and treatments at a scale and speed previously impossible in the U.K.," said Jensen Huang, founder and chief executive officer of Nvidia, in a statement.
	</blockquote>		</blockquote>

Admin at 09:25, 15 July 2021

2021-07-15T09:25:11Z

← Older revision		Revision as of 09:25, 15 July 2021
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	China has set its sights on building a domestic AI industry worth nearly $150 billion in the next few years and of becoming the leading AI power by 2030.		China has set its sights on building a domestic AI industry worth nearly $150 billion in the next few years and of becoming the leading AI power by 2030.
			</blockquote>

			==2021.07.05 China beats Google to claim the world's most powerful quantum computer==

			'''Matthew Sparkes. NewScientist. 5 July 2021. <span class="plainlinks">https://www.newscientist.com/article/2282961-china-beats-google-to-claim-the-worlds-most-powerful-quantum-computer/</span>'''

			<blockquote>
			A team in China has demonstrated that it has the world's most powerful quantum computer, leapfrogging the previous record holder, Google.

			Jian-Wei Pan at the University of Science and Technology of China in Hefei and his colleagues say their quantum computer has solved a problem in just over an hour that would take the world's most powerful classical supercomputer eight years to crack, and may yet be capable of exponentially higher performance.
	</blockquote>		</blockquote>

Admin at 07:12, 13 July 2021

2021-07-13T07:12:49Z

← Older revision		Revision as of 07:12, 13 July 2021
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	</blockquote>		</blockquote>

	=The ~~press~~=		=The Press=

	==2021.07.09 China Targets AI Dominance by 2030==		==2021.07.09 China Targets AI Dominance by 2030==