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Trades by Robot cost Hong Kong businessman $20mn, who does he sue?

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Robots are getting more humanoid every day, but they still can’t be sued.

So a Hong Kong tycoon is doing the next best thing. He’s going after the salesman who persuaded him to entrust a chunk of his fortune to the supercomputer whose trades cost him more than $20 million.

The case pits Samathur Li Kin-kan, whose father is a major investor in Shaftesbury Plc, which owns much of London’s Chinatown, Covent Garden and Carnaby Street, againstRaffaele Costa, who has spent much of his career selling investment funds for the likes of Man Group Plc and GLG Partners Inc. It’s the first-known instance of humans going to court over investment losses triggered by autonomous machines and throws the spotlight on the “black box”problem: If people don’t know how the computer is making decisions, who’s responsible when things go wrong?

“People tend to assume that algorithms are faster and better decision-makers than human traders,”saidMark Lemley, a law professor at Stanford University who directs the university’s Law, Science and Technology program. “That may often be true, but when it’s not, or when they quickly go astray, investors want someone to blame.”

The timeline leading up to the legal battle was drawn fromfilingsto the commercial court in London where the trial is scheduled to begin nextApril. It all started over lunch at a Dubai restaurant on March 19, 2017. It was the first time 45-year-old Li, met Costa, the 49-year-old Italian who’s often known by peers in the industry as “Captain Magic.”During their meal, Costa described a robot hedge fund his company London-based Tyndaris Investments would soon offer to manage money entirely using AI, or artificial intelligence.

Developed by Austria-based AI company 42.cx,the supercomputer named K1would comb through online sources like real-time news and social media to gauge investor sentiment and make predictions on U.S. stock futures. It would then send instructions to abroker to execute trades, adjusting its strategy over time based on what it had learned.

The idea of a fully automated money manager inspired Li instantly. He met Costa for dinner three days later, saying in an e-mail beforehand that the AI fund “is exactly my kind of thing.”

Over the following months, Costa shared simulations with Li showing K1 making double-digit returns, although the two now dispute the thoroughness of the back-testing. Li eventually let K1 manage $2.5 billion—$250 million of his own cash and the rest leverage from Citigroup Inc. The plan was to double that over time.

But Li’s affection forK1 waned almost as soon as the computer started trading in late 2017. By February 2018, it was regularly losing money, including over $20 million in a single day—Feb. 14—due to a stop-loss order Li’s lawyers argue wouldn’t have been triggered if K1 was as sophisticated as Costa led him to believe.

Li is now suing Tyndaris for about $23 million for allegedly exaggerating what the supercomputer could do. Lawyers for Tyndaris, which is suing Li for $3 million in unpaid fees, deny that Costa overplayed K1’s capabilities. They say he was never guaranteed the AI strategy would make money.

Sarah McAtominey, a lawyer representing Li’s investment company that is suing Tyndaris, declined to comment on his behalf. Rob White, a spokesman for Tyndaris, declined to make Costa available for interview.

The legal battle is a sign of what’s in storeas AI is incorporated into all facets of life, from self-driving cars to virtual assistants. When the technology misfires, where the blame lies is open to interpretation. In March, U.S. criminal prosecutors let Uber Technologies Inc.off the hookfor the death of a 49-year-old pedestrian killed by one of its autonomous cars.

In the hedge fund world, pursuing AI has become a matter of necessity after years of underperformance byhuman managers. Quantitative investors—computers designed to identify and execute trades—are already popular. More rare are pure AI funds that automatically learn and improve from experience rather than being explicitly programmed.Once an AI develops a mind of its own, even its creators won’t understand why it makes the decisions it makes.

“You might be in a position where you just can’t explain why you are holding a position,”saidAnthony Todd, the co-founder of London-based Aspect Capital, which is experimenting with AI strategies before letting them invest clients’ cash. “One of our concerns about the application of machine-learning-type techniques is that you are losing any explicit hypothesis about market behavior.”

Li’s lawyers argue Costa won his trust by hyping up the qualifications of the technicians building K1’s algorithm, saying, for instance, they were involved in Deep Blue, the chess-playing computer designed by IBM Corp. that signaled the dawn of the AI era when it beat the world champion in 1997. Tyndaris declined to answer Bloomberg questions on this claim, which was made in one of Li’s more-recent filings.

Speaking to Bloomberg,42.cx founderDaniel Mattessaid none of the computer scientists advising himwere involved with Deep Blue, but one,Vladimir Arlazarov, developed a 1960s chess program in the Soviet Union known as Kaissa. He acknowledged that experience may not be entirely relevant to investing. Algorithms have gotten really goodat beating humans in games because there are clear rules that can be simulated, something stock markets decidedly lack. Arlazarov told Bloomberg thathe did give Mattes general advice but didn’t work on K1 specifically.

Inspired by a 2015 European Central Bank study measuring investor sentiment on Twitter,42.cxcreated software that could generatesentiment signals, said Mattes, who recently agreedto pay $17 million to the U.S. Securities and Exchange Commission to settle charges of defrauding investors at his mobile-payments company, Jumio Inc., earlier this decade. Whether and how to act on those signalswas up to Tyndaris, he said.

“It’s a beautiful piece of software that was written,” Mattes said by phone. “The signals we have been provided have a strong scientific foundation. I think we did a pretty decent job.I know I can detect sentiment. I’m not a trader.”

There’s a lot of back and forth in court papers over whether Li was misled about K1’s capacities. For instance, the machine generated a single trade in the morning if it deciphered a clear sentiment signal, whereas Li claims he was under the impression it would make trades at optimal times during the day. In rebuttal, Costa’s lawyers say he told Li thatbuying or selling futures based on multiple trading signals was an eventual ambition, but wouldn’t happen right away.

For days, K1 made no trades at all because it didn’t identify a strong enough trend. In one message to Costa, Li complained that K1 sat back while taking adverse movements “on the chin, hoping that it won’t strike stop loss.”A stop loss is a pre-set level at which a broker will sellto limit the damage when prices suddenly fall.

The legal battle is a sign of what’s to come as AI is incorporated into all facets of life

That’s what happened on Valentine’s Day 2018. In the morning, K1 placed an order with its broker, Goldman Sachs Group Inc., for $1.5 billion of S&P 500 futures, predicting the index would gain. It went in the opposite direction when data showed U.S.inflationhad risen more quickly than expected, triggering K1’s 1.4 percent stop-loss and leaving the fund $20.5 million poorer. But the S&P rebounded within hours, something Li’s lawyers argue shows K1’s stop-loss threshold for the day was “crude and inappropriate.’

Li claims he was told K1 would use its own “deep-learning capability” daily to determine an appropriate stop lossbased on market factors like volatility. Costa denies sayingthis and claims he told Lithe level would be set by humans.

In his interview,Mattes saidK1 wasn’t designed to decide on stop losses at all—only to generate two types of sentiment signals: a general one that Tyndaris could have used to enter a position and a dynamic one that it could haveused to exit or change a position.While Tyndaris also marketed a K1-driven fund to other investors, a spokesman declined to comment on whether the fund had ever managed money. Any reference to the supercomputer was removed from its website last month.

Investors likeMarcus Storrsay they’rewary when AI fund marketers come knocking,especially considering funds incorporating AI into their core strategy made less than half the returns of the S&P 500 in the three years to 2018, according to Eurekahedge AI Hedge Fund Index data.

“We can’t judge the codes,” said Storr, who decides on hedge fund investments for Bad Homburg, Germany-based Feri Trust GmbH. “For us it then comes down to judging the setups and research capacity.”

But what happens when autonomous chatbots are used by companies to sell products to customers? Even suing the salesperson may not be possible, addedKarishma Paroha, a London-based lawyer at Kennedys who specializes in product liability.

“Misrepresentation is about what a person said to you,” she said. “What happens when we’re not being sold to by a human?”

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Zepto, 10-minute grocery delivery app, raises $100 million

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Only five months subsequent to dispatching, 10-minute basic food item conveyance application Zepto on Tuesday reported it has raised $100 million driven by Y Combinator, taking its valuation to $570 million.

Other than the raise money, Zepto has been developing staggeringly rapidly and is significantly increasing its client base consistently.

In the course of recent months, Zepto has extended past Mumbai by dispatching in Bengaluru, Delhi, Gurgaon, Chennai, Hyderabad, and Pune (Kolkata to follow), the organization said in an assertion.

“Financial backers are reliably deciding to back Zepto due to our top tier execution. This is giving us extraordinary energy – we’re developing at an amazing rate, clients are adoring the item experience, our center unit financial matters are solid, and we have one of the most outstanding startup groups in India today,” said Aadit Palicha, Co-Founder and CEO.

The Series C raising money round saw support from new and existing financial backers, including Glade Brook, Nexus, Breyer Capital, Lachy Groom, Global Founders Capital, Contrary Capital, and that’s just the beginning.

The round came 45 days later the organization reported its $60 million raise money in November.

Conveying food in a short time is a game-changing encounter for clients in the nation, and a few players are presently joining the race.

“We are eager to twofold down and lead this round in Zepto. They initially dispatched with an alternate model, quickly turned to speedy trade in August 2021, and are presently adding 100,000 new clients consistently, 60% of the ladies,” said Anu Hariharan from Y Combinator.

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One stuck box of fertilizer shows the global supply chain crisis

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Somewhere in the world’s busiest port of Shanghai, a container of fertilizer sits among tens of thousands of boxes, waiting for a ride to the U.S. It’s been on the dock for months, trapped by typhoons and Covid outbreaks that have worsened major congestion in the global supply-chain network.

While the fertilizer has been stranded there since May, the port is just one stop on the long journey from central China to the U.S. Midwest. Delays have stretched a delivery that ordinarily would take weeks to more than half a year. And that time frame will keep expanding, as the goods have barely started the roughly 15,000 kilometer (9,300 mile) trek.

This is the tale of one humble shipment and its arduous journey across the world. While some of the barriers keeping it from its final destination may be specific to this particular case, the journey is emblematic of the inertia that has gripped global trade during the pandemic.

From the U.S. to Sudan to China, container boxes have been lying at ports, railyards and in warehouses as the pandemic rages on. In an industry with 25 million containers and some 6,000 ships hauling them, it’s easy to see disruptions as one big headache confined to the shipping world. But each container that’s delayed is economic activity that’s restrained, heaping costs one box at a time on consumers and making it more challenging to put corn on consumers’ tables or deliver presents for the holidays.

It’s also a lesson in the ripple effects across global supply chains, showing the limits of diversification as all networks are still closely connected with China.

“All roads lead back to China, and that has a major effect across the entire supply chain,” said Dawn Tiura, head of U.S.-based Sourcing Industry Group. “Congestion at one port or factory has far-reaching implications for neighboring facilities, which trickles out across the world.”

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Bharat Biotech’s BBV154 leads global race for intranasal COVID-19 vaccine

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Bharat Biotech’s nasal COVID-19 vaccine candidate BBV154 has become the front runner globally to likely commercialise an intranasal vaccine, following green signal from the government to conduct a combined Phase II and III final clinical trials in India. At present out of the 110 vaccines under clinical development globally, only eight are intranasal vaccines and three are oral vaccines. So far none of these vaccines have entered the final phase of trials and most are still in the first phase.

BBV154 is an intranasal replication-deficient chimpanzee adenovirus SARS-CoV-2 vectored vaccine, in-licensed from the Washington University in St Louis, USA. Nasal and oral vaccines are expected to be a game-changer second-generation COVID-19 vaccine, as they stimulate a broad immune response and prevent both infection and transmission. The non-invasive, needle-free vaccines do not require trained health care workers to administer the vaccine, have no risks of injuries and infections and is suited for children and adults. Unlike Covaxin, which is difficult to make, manufacturing can be scaled up fast and easily.  Compared to injectable vaccines, nasal and oral vaccines are expected to provide long-lasting protection.

Bharat Biotech is yet to announce its plans and timeline for the nasal vaccine’s future development.

Serum Institute of India and Codagenix have done a 48-subject Phase I clinical trial in the UK for an intranasal COVID-19 vaccine, COVI-VAC. This live attenuated candidate vaccine is expected to have potential to provide a broader immune response, in comparison to most COVID-19 vaccines that target only a portion of the virus. Codagenix has recently completed dosing for its Phase I trials and data is expected to come out in the third quarter of the year.

Nasdaq listed US biopharmaceutical company Altimmune, which was developing a three-dose intranasal vaccine candidate  AdCOVID, discontinued the project on July 29, as its first phase trials did not stimulate an adequate immune response in healthy volunteers. “The top-line Phase 1 clinical data are disappointing given the encouraging preclinical data and our substantial efforts in advancing a differentiated, intranasal vaccine candidate in the fight against COVID-19,” said Vipin K Garg, Altimmune’s India born President and Chief Executive Officer.

The University of Hong Kong, Xiamen University and Beijing Wantai Biological Pharmacy in China are trying a Phase II clinical trial of a two-dose influenza virus vector COVID-19 vaccine as an intranasal spray (DelNS1-2019-nCoV-RBD-OPT1). Its one year long second phase trial among 240 volunteers is going on and will conclude only by mid-December 2021.

The University of Oxford is conducting a single dose Phase I study of AstraZeneca’s ChAdOx1 nCOV-19 (Covishield in India and manufactured by the Serum Institute) to be administered intranasal among 54 volunteers in three groups. According to the trial design, the study started in April is estimated to complete the first phase only by February 2022.

Cuban government’s Center for Genetic Engineering and Biotechnology, which developed Latin America’s first COVID-19 vaccine Abdala, is undertaking a Phase I/II study of an intra-nasal three dose protein subunit vaccine candidate Mambisa (CIGB-669). According to the research agency, Mambisa is based on the formulation of the RBD (Receptor Binding Domain) protein and an immuno enhancer, Hepatitis B nucleocapsid antigen.

Canadian biotech Symvivo Corporation has ‘bacTRL-Spike’, as an oral capsule DNA vaccine candidate for the prevention of COVID-19, is undergoing Phase I trials in Australia. The trial was started only in November, last year. The global drug major Merck, known as MSD outside the United States and Canada, has taken exclusive license of Symvivo’s bacTRL platform of oral vaccines.  Symvivo has funding of about $4.57 million from the National Research Council of Canada Industrial Research Assistance Program (NRC IRAP) to develop this vaccine.

US biotech Meissa Vaccines’s MV-014-212, a single dose intranasal recombinant live attenuated COVID-19 vaccine, is undergoing Phase I trials and its interim trial data will come out by the end of this year. Another small US biotech, Vaxform and the US Specialty Formulations LLC (USSF) are developing an oral COVID-19 vaccine, which is also in its first phase. Similarly, another US small biotech CyanVac LLC is also attempting an intranasal parainfluenza virus based COVID-19 vaccine (CVXGA1), now in the first phase and its results are also expected only by the end of the year.

Mexican veterinary pharmaceutical company Laboratorio Avi-Mex is testing a live influenza virus based vaccine, both as an intranasal spray as well as an injection. It is starting Phase I trials and is funded by Mexico’s foreign ministry and the National Council of Science and Technology (Conacyt). The Mexican authorities hope to commercialise this vaccine by the end of the year.

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