Thursday, March 02, 2023

 Computer Artificial Intelligence Ai Dall-E Chatgpt

Generative AI And Large Language Models: The AI Gold Rush – Analysis

  

By 

By Dr. Sanur Sharma*

Summary

Generative Artificial Intelligence (AI) models have a vast application landscape and use cases as they can help enterprises automate intelligence through a knowledge base across multiple domains. These models can help scale up innovation in AI development across sectors. Negative use cases of generative AI include disinformation spread and influence operations. Organisations and governments are attempting to address these concerns through practices like responsible data collection, ethical principles for AI, and algorithmic transparency.

The democratisation of Artificial Intelligence (AI) with new technology platforms is gaining significant importance, with tech giants like Google, Microsoft and Baidu challenging each other in the business of Generative AI. The Large Language Models (LLMs) and Generative AI models like OpenAI’s ChatGPT, which has been put out in the public domain, have created a stir online and within communities about the possibilities of AI replacing humans. The expansion of LLMs has gained momentum in the past two years with the introduction of AI-based chatbots and conversational agents taking the online marketplace. 

Their ability to handle diverse tasks like answering complex questions, generating text, sounds, and images, translating languages, summarising documents, and writing highly accurate computer programmes has brought them into the public eye. These models can synthesise information from billions of words from the web and other sources and give a sense of fluid interaction. Amidst the hype around these models, the less debated issue is the possibility of these tools generating falsehoods, biases, and other ethical considerations. 

Generative AI models 

Generative AI systems refer to the class of machine learning where the system is trained to generate new data or content like audio, video, text, images, art, music, or an entire virtual world of things. These models study the statistical patterns and structures from the training data and discover new information on different samples that resembles the original data. In addition, these models are trained on humongous amounts of data; they seem creative when they produce a variety of unexpected outputs that make them look genuine. 

Various Generative AI models include Variational Autoencoders, Auto Aggressive Models, and Generative Adversarial Networks. Generative AI models have varied applications today, from image generation to music creation, data augmentation and more. The area gaining the most significance today is the text generation tools, also known as large language models. Various leading companies and labs are doing R&D in this field. 

The LLM originated in 2017, and one of the first such models was Bidirectional Encoder Representation from Transformer (BERT) and Generative Pre-trained Transformer (GPT) by Google and OpenAI, which were open-sourced in the same year. Following the idea, many such models originated, like OpenAI’s GPT2, PaLM 540B, Megatron 530B, GitHub’s Copilot, Stable Diffusion, and InstructGPT.1 More recently, next-generation tools like ChatGPT, DALL-E-2 and Google’s Language Model for Dialogue Applications (LaMDA) have become the internet sensation. These LLMs are trained on large amounts of data (petabytes) and are used for zero-shot or few-shot scenarios where little domain knowledge is available, so they can start generating data based upon just a few prompts. For instance, OpenAI’s GPT-3 is a 175 billion parameter model and can generate text and code from a very short prompt.2 

The Generative AI models have a vast application landscape and use cases. Therefore, these models can help enterprises automate intelligence through a knowledge base across multiple domains shown in Figure 1. In addition, these models have the capability to scale up innovation in AI development across sectors.

Source: By Author
Source: By Author

ChatGPT

ChatGPT is a generative AI based on transformer architecture that generates natural language responses to the given prompt. It is a type of autoregressive model that produces a sequence of text based on the previous tokens in sequence. ChatGPT has revolutionised people’s interaction with technology so that it seems as if one person is talking to another person.

It was first introduced in 2018 by OpenAI and is based upon InstructGPT with changes in data collection setup, and in November 2022, it was made public for user feedback. Mesmerised users posted on social media what this chatbot can do—like producing code, writing essays, poems, speeches, and letters—even creating fear among content writers of losing their jobs. However, the full scope of these tools is yet to be determined as there are risks associated with this technology that need to be addressed. 

GPT tools have been in the market before and are used for various use cases. These models have gone through a series of improvements over time. Figure 2 presents the timeline of OpenAI’s GPT models.

Source: By Author
Source: By Author

ChatGPT has a broad range of applications like expert conversational agents, language translation and text summarisation, to state a few. It can also learn and adapt to new contexts and situations by analysing text and updating its algorithm based on new data. This continuous analysis makes it more accurate in generating responses. It is based on reinforcement learning with human feedback (Figure 3).3 The model is trained using supervised fine-tuning with human AI trainers providing conversations. The reward model works on comparison data built from the conversations of AI trainers with the chatbot and the ranking of the sampled alternative messages. The model has been fine-tuned by using Proximal Policy Optimisation. ChatGPT is the fine-tuned model of the GPT-3.5 series that completed its training in 2022. Both these models have been trained on Azure AI supercomputing Infrastructure.4

Source: Adapted by Author from OpenAI.5

One of the key benefits of ChatGPT is its power to process and learn from interactions with users, understanding the context and nuances of the language and coming out with meaningful and accurate responses. It can constantly improve itself through conversations and building its extensive database. Therefore, one can expect more remarkable capabilities from this model in the future. Furthermore, it is modelled on deep learning architecture, which allows it to achieve a higher level of accuracy in content creation.

The training data of ChatGPT is collected from vast data sources like web pages, books, scientific articles, and corpora of text from other sources. The model is trained on 570 GB of data, about 300 billion words.6 The cut-off for this data collection was in 2021,7 and specific training data was used, which might impact the model’s performance in terms of generating relevant responses that are contextually appropriate. This implies that the model lacks real-time data and analysis and information post-2021. In addition, behind this colossal dataset and training, there are some issues that ChatGPT still needs to address, which includes an improved response mechanism in terms of additional layers in the model for verification and validation to present more meaningful information.

Race to Build Generative AI and LLMs

The overwhelming response to models like ChatGPT, LaMDA and DALL-E-2 has stirred the industry and started a race amongst the tech giants to build such models as a significant part of the search engine business. 

Google’s LaMDA was developed in 2020 and is based on Transformer, a neural network architecture8 that gained popularity in 2022 when an engineer from Google went public and termed it a sentient system. The much-hyped generative AI Chatbot is said to have been considered more capable than ChatGPT, but until it is publicly released, it is difficult to prove the same. On 6 February, Google announced another AI chatbot ‘Bard’, a conversational AI as a rival to OpenAI’s ChatGPT.9 It is said to be capable of responding to human queries and synthesising information like ChatGPT and is a lightweight version of Google’s LaMDA. However, within days of the launch, the flaw in Bard was noticed where the tool made a factual error in one of its promotional videos. Following this, Google’s share dropped by 9 per cent and the company lost around US$ 100 billion in market value. Google’s Vice President of Search Prabhakar Raghavan asked the trainers and executives to rewrite Bard’s incorrect responses. Google is also investing US$ 300 million in Anthropic, an AI startup to work in the field of Generative AI.10 Some other generative AI models by Google are MUM, PaLM and MusicLM. 

Microsoft is also said to be investing billions of dollars in AI and revamping its search engine Bing and Edge web browser with AI capabilities.11 It is working in collaboration with OpenAI and is looking at integrating ChatGPT into Bing and further commercialise its Azure OpenAI service with several AI models like GPT3.5, Codex and DALL-E and the soon to be released GPT4.12 On 7 February, Microsoft launched the AI-powered Bing search engine and Edge browser for preview as an AI co-pilot for the web to get more people to benefit from search and web. The users asked questions to Bing, and it gave direct answers in chat and not with links to websites. The users with access to this feature were curious to have prolonged interactions with the search engine, which then got deranged and started expressing emotions of love and anger. 

Following this, Microsoft put a cap of five questions per session and 50 questions per day, as it was observed that only 1 per cent of users have more than 50 questions in a day.13 The company stated that the tool needed training to be more reliable. In future, it will introduce a toggle mode allowing users to select the level of creativity they wish to have in their responses.14 In the past, DALL-E2, a text-to-image generator, faced a similar glitch where the tool was said to create its own language and struggled to generate coherent images of text.

The big tech companies investing in Generative AI tools indicate the promise these tools present and the profound benefits users experience when they come across meaningful writings and content that seems to incur human annotation. These tools will bring ease in doing business with multiple use cases in various sectors like devising personalised marketing, social media and sales content; code generation, documentation and content creation in IT; pulling out data, summarising and drafting of legal documents; enabling R&D in drug discovery; providing self-serve functions in Human Resources (HR) and assisting in content creation for questionnaires and interviews; employee optimisation through automated responses, text translation, crafting presentations and synthesising information from video meetings; and creating assistants for specific businesses.15 

In the future, these tools are expected to generate their own data by bootstrapping their own intelligence and fine-tuning it for better performance. All these tools are based on an autoregressive transformer model and are dense, which means that they use all the parameters (millions/billions) to produce a response. The research in this aspect is now moving towards designing models that will only use the relevant parameters to generate a response, making them less computationally difficult.16 

The race among the tech giants to come out with these tools is like the innovators’ dilemma to rule the search engine business. The reasons behind this hurry to come out with such tools could be either to take the lead in this business and vision for the future or to collect more data from human users and keep training their models to perform better. Nevertheless, adopting these tools will be part of the businesses soon, but criticism over their shortcomings will also follow.

Implications of Generative AI Models

The challenge with Generative AI models is to ensure that the generated data is of good quality, balanced, free from potential biases and a good representative of the original data. These models present a risk of overfitting and generation of unrealistic data, which raises ethical concerns related to using such models. Last year, Google’s chatbot LaMDA was claimed as sentient by their engineers,17 and OpenAI’s DALLE-2 talking gibberish was said to have created its own language.

Another issue with these Generative AI systems is that cybercriminals have started to use these tools to develop malicious codes and tools. According to Check Point Research (CPR), major underground hacking communities are already using OpenAI to create spear-phishing emails, infostealers, encryption tools, and other fraud activities. The dark web is being used by the hackers for posting the benefits of malware and for sharing code (like for generating stealers) with the help of tools like ChatGPT.18 

One of the negative use cases of Generative AI is spreading disinformation, shaping public perception and influence operations. These language models have the capability to automate the creation of misleading text, audio and videos to spread propaganda by various malicious actors. A report by CSET and OpenAI discusses the three dimensions (actors, behaviours and content) where language models and Generative AI can be used for targeted influence operations.19 Considering the pace of development in this field, these models are likely to become more usable, efficient and cost-effective with time, making it easier for the threat actors to use them for malicious activities.

Currently, organisations and governments/countries are attempting to address these concerns through practices like responsible data collection, ethical principles for AI, and algorithmic transparency. Moreover, the legal implications of using AI models are also under consideration, specifically on regulations and guidelines for various sectors like healthcare, finance, and defence—where data privacy, security, and regulation on the use of AI for decision-making are of utmost importance.

At present, there are no regulations that apply to LLMs or AI language models in particular. However, there is a need to spread awareness amongst various stakeholders and civil society to consider the ethical and legal implications of these technologies and ensure that appropriate frameworks are implemented for its responsible use. Countries are striving towards establishing AI strategies and data protection laws, focusing on establishing regulations on AI governance and its ethical use. A few such initiatives by OECD are its ethical principles on AI and support to other countries and organisations in establishing AI principles and best practices.20 

The European Union’s (EU) data protection law is another act that closely observes the privacy issues related to data and algorithms.21 EU is also moving fast with its draft of the AI act that intends to govern all AI use cases.22 The US is also working towards AI governance and has come out with various policies and principles like the 2023 US National Defense Authorization Act (NDAA), which has proposed provisions for governing and deploying AI capabilities. Sections 7224 and 7226 relate to principles and policies for the use of AI in government and rapid deployment and scaling of applied AI for modernisation activities with use cases.23 The US National Institute of Standards and Technology (NIST) has also issued Version 1.0 of its AI Risk Management Framework (AIRMF 1.0), which is a multi-tool for organisations to design and deploy trustworthy AI.24 Recently, China has come out with a series of regulations specific to different types of algorithms and AI capabilities, including relating to AI algorithms for Deepfakes.25

Conclusion

Generative AI systems have the potential to revolutionise the way we work and live. Its capability to cater to diverse audiences with meaningful information in a contextualised manner and provide tailor-made responses has brought a significant breakthrough in technology and how we use it. As these tech companies dive into the foray of these AI applications and use cases, it is imperative to study the implications of this technology and how it affects society at large. The regulation of AI systems is still in its infancy, and countries looking at building their own policies and regulations can learn from the positives and negatives of the two different models being implemented by the EU and China. 

The next wave of innovation in Generative AI and LLMs will bring new use cases and applications in other domains with better reliability mechanisms. These AI tools certainly have limitless potential, but at the same time, they should not be totally relied upon as a replacement for human decision-making as they lack emotional intelligence and human intuition and struggle with language nuances and context, with the risk of biases being introduced at any point in their structural mechanisms. There is no silver bullet solution with Generative AI systems, and hence coordination among stakeholders, civil society, government and other institutions is needed to manage and control the risks associated with this technology.

Views expressed are of the author and do not necessarily reflect the views of the Manohar Parrrikar IDSA or of the Government of India.

*About the author: Dr Sanur Sharma is Associate Fellow at Manohar Parrikar Institute for Defence Studies and Analyses.

Source: This article was published by Manohar Parrrikar IDSA


Manohar Parrikar Institute for Defence Studies and Analyses (MP-IDSA)

The Manohar Parrikar Institute for Defence Studies and Analyses (MP-IDSA), is a non-partisan, autonomous body dedicated to objective research and policy relevant studies on all aspects of defence and security. Its mission is to promote national and international security through the generation and dissemination of knowledge on defence and security-related issues. The Manohar Parrikar Institute for Defence Studies and Analyses (MP-IDSA) was formerly named The Institute for Defence Studies and Analyses (IDSA).
Posted by at No comments:

Wednesday, March 01, 2023

Myanmar: Junta Troops Raze Entire Village In Sagaing Region

Kone Ywar village was nearly burned to the ground by Myanmar junta forces during a night raid Tuesday, Feb. 28, 2023, in Yinmarbin township, Sagaing region.
 Photo Credit: Citizen journalist, via RFA

March 2, 2023
By RFA


The junta troops entered the central Myanmar village of Kone Ywar on Tuesday evening and set it alight. When the flames had finally died down by Wednesday morning, they methodically set fire to whatever was left standing.

The destruction in Kone Ywar – a settlement populated by more than 1,400 people in Sagaing region’s embattled Yinmarbin township – is becoming all too commonplace in Myanmar, where more than two years after a coup, the military has embarked on a scorched earth campaign to root out the country’s armed resistance.

But while civilians are regularly caught up in the conflict, despite claims by the junta that it does not target noncombatants, it is rare for the military to wipe out nearly an entire village.

By the time the smoke had cleared on Wednesday and the junta unit had moved on, all but 30 of Kone Ywar’s more than 700 homes had been razed, three civilians had been killed, and thousands of Yinmarbin’s residents had fled the township in fear for their lives.

“[The soldiers] burned down almost the entire village … They were burning the whole night yesterday and they even torched the houses left standing this morning,” a resident, who spoke on condition of anonymity fearing reprisal, told RFA Burmese.

“Only about 30 houses were left, although we don’t know exactly how many were destroyed.”

The raid followed a clash near the entrance to Kone Ywar between the military and members of the local anti-junta People’s Defense Force paramilitary group that led to military casualties, he said, suggesting that the arson had been an act of revenge.

Other residents told RFA that the soldiers had killed three men in their 30s, two of whom lived in Kone Ywar. The identity of the third man was not immediately clear.

Soon after departing Kone Ywar, the troops again clashed with PDF forces in nearby Yae Aungt village, with military helicopters joining the battle, they said.

Around 10,000 residents from the two villages, as well as from others in the vicinity – including Sar Taw Pyin, Zee Taw, Let Hloke, Ohn Taw, Lar Boet and Yin Paung Taing – had fled their homes for safety and remained displaced, residents added.

Yinmarbin is one of the townships in Sagaing region declared under martial law by the junta last month.

Wetlet township raid

The destruction in Kone Ywar came on the same day that junta troops raided two villages in Sagaing’s Wetlet township, setting fire to homes and killing at least two elderly residents, sources said.

A resident of Wetlet, who declined to be named citing security concerns, told RFA that a column of around 80 soldiers torched 59 houses in Moke Soe Chon Bu Tar and another two homes in nearby Bo Te on Tuesday.

Tin Hla, a woman in her 70s, perished in the fires in Bo Te, the resident said.

“They left her there when they were burning the houses and since she was too old to run, she died in the fire,” he said.

Junta troops leaving Moke Soe Chon Bu Tar at around 8:00 a.m. on Wednesday shot and killed Myint Than, 60, as he rode his motorbike outside the village, the resident said.

More than 1,000 residents of the two villages – each with more than 100 homes – were forced to flee to safety during the raid, sources told RFA.

Attempts by RFA to contact Aye Hlaing, the junta’s social affairs minister for Sagaing region, by phone went unanswered Wednesday. However, junta Deputy Information Minister Major Gen. Zaw Min Tun has previously said that arson is a tactic used by the PDF and that the military “never causes harm to civilians.”

Last month, a military column burned down more than 100 houses in Wetlet township’s Ta Kaung Min village in a Feb. 3 raid, during which a civilian was killed by a rocket propelled grenade fired by junta soldiers, residents said.

According to the United Nations Office for the Coordination of Humanitarian Affairs, as of Feb. 2, some 650,000 residents of Sagaing region had fled their homes due to armed conflict in the aftermath of the Feb. 1, 2021, coup.

Data for Myanmar, an independent research organization, says that at least 43,292 houses have been destroyed by arson in Sagaing in the two years since the takeover.

Translated by Myo Min Aung. Edited by Joshua Lipes and Malcolm Foster.


RFA
Radio Free Asia’s mission is to provide accurate and timely news and information to Asian countries whose governments prohibit access to a free press. Content used with the permission of Radio Free Asia, 2025 M St. NW, Suite 300, Washington DC 20036.
Posted by at No comments:
California bill would help protect nannies, house cleaners

By Sophie Austin | AP
March 1, 2023 



 Domestic workers in California don’t have the same safety protections required by law for many employees in case they get injured or sick on the job. But state lawmakers are trying to change that in their latest attempt to expand these workers’ rights in a bill being introduced by Sen. Durazo. 

SACRAMENTO, Calif. — California households that employ cleaners or nannies could soon be required to comply with safety standards similar to other workplaces under a bill proposed in the state Legislature.

Domestic workers in California don’t have the same safety protections required by law for many employees in case they get injured or sick on the job. A bill by Democratic state Sen. María Elena Durazo would give those hired by private employers to do domestic work protections under the California Occupational Safety and Health Act. The legislation would not apply to domestic work paid for by the government.

On Wednesday, domestic workers came from across California to voice their support for the legislation at the state Capitol, where some held up a sign in Spanish that read, “Everyone Deserves a Safe Workplace.”

Durazo, who represents central Los Angeles, noted the symbolism of the gathering taking place on the first day of Women’s History Month. She said she hopes lawmakers take action to protect a sector of the workforce made up largely of women of color.

“Women’s work needs to be treated just as important as any other work,” she said.

Nearly 92% of domestic workers in the United States are women, and more than half are Black, Hispanic or Asian American, the Economic Policy Institute estimated in 2020.

“Domestic work is important work, and these workers deserve all of the rights and protections afforded to workers in other industries,” said Anna Pisarello, a teacher who employs a nanny to take care of her two children.

In recent years, supporters of these types of protections have made strides to increase safety for domestic workers, a group hit hard during the pandemic, who are particularly susceptible to getting hurt or sick from work.

In New York, Democratic Gov. Kathy Hochul signed a bill into law in 2021 protecting these workers under a state human rights law. But in Virginia, lawmakers tried and failed to pass a bill that same year that would have included these workers in an employee protection law.

In California, Democratic Gov. Gavin Newsom vetoed a similar bill in 2020, citing the burden on private employers to comply with state worker safety law regulations. In 2021, he signed a bill that created an advisory committee that submitted a list of recommendations to the Legislature in January, which included a financial assistance program to help employers with the cost of making sure their home is safe to work in.

If the bill introduced last month becomes law, the state’s Division of Occupational Safety and Health would have to come up with standards by July 1, 2024 to help employers comply with requirements. Employers would then have to comply with regulations by Jan. 1, 2025. The legislation would also create a program to give grants to employers who can use the money to make sure their home is safe for workers.

Martha Herrera, who cleans houses and takes care of children in San Francisco, said she used to look after a girl with autism between the time she was 4 to 8 years old. That included giving her baths and carrying her to the bathroom, she said. One day, the girl almost fell in the shower, and Herrera moved to catch her. As a result, Herrera started to feel a pain in her waist.

After Herrera’s employers paid her for her work and gave her $300 for medicine, she was unable to work for three months because of the pain, she said.

“This experience motivated me to continue to fight for the rights of domestic workers,” said Herrera, who is also a member of the domestic worker policy advisory committee.

Mariko Yoshihara, a lawyer and policy director with the California Employment Lawyers Association, said domestic workers should have been given these protections a long time ago.

“The fact that there is one categorical exclusion in our health and safety laws specifically for domestic workers is just unjust,” she said.

___

Sophie Austin is a corps member for the Associated Press/Report for America Statehouse News Initiative. Report for America is a nonprofit national service program that places journalists in local newsrooms to report on undercovered issues. Follow Austin on Twitter: @sophieadanna
Posted by at No comments:



China warns ‘hedonistic’ bankers to toe the Communist Party line

Mr He Lifeng is being considered for the role of party secretary at the People’s Bank of China. PHOTO: REUTERS

BEIJING – Bankers in China are being told to rectify their mindsets, clean up their “hedonistic” lifestyles and stop copying Western ways.

The directives, part of a 3,500-word commentary last week from the country’s top anti-graft watchdog, is just the latest sign that President Xi Jinping’s campaign to tighten the Communist Party’s grip on the financial system has a long way to go.

As the National People’s Congress kicks off this weekend, Mr Xi is poised to further entrench control by reviving a powerful committee to coordinate economic and financial policy and installing close allies to oversee it all.

That comes on the heels of the sudden disappearance of one of China’s top investment bankers and follows the downfall of dozens of officials over the past 18 months in the most sweeping corruption crackdown on financial sector ever.

In its warning last week, China’s Central Commission for Discipline Inspection said bankers should abandon pretensions of being the “financial elite”.

“All of these development speak to one thing: the Communist Party will govern everything, including economic and financial work,” said Mr Shen Meng, a director of Beijing-based investment bank Chanson & Co. “Policy makers are placing the finance industry at the heart of the economy as a lubricant for its smooth development, and if the economy goes sour, the sector is mainly to blame.”

This is a critical moment for Mr Xi as he seeks to reign in risks in the $60 trillion financial sector (S$80.7 trillion) – imposing stricter controls on capital outflow, controlling debt levels and ruling out risky practices – while he tries to restore growth and manage the economic fallout of spiralling ties with the US.

Aiming criticism at the industry may well provide Mr Xi with convenient cover if that doesn’t go smoothly.

The National People’s Congress – where top leaders will assess the government’s past performance and outline policies for the year ahead – offers Mr Xi his first opportunity to shake up state institutions since he secured a precedent-breaking third term at the party’s twice-a-decade congress.

China’s top leaders have typically used the first parliament meeting after a congress to reorganise critical government organs. In 2018, Mr Xi carried out the most extensive overhaul in decades in a revamp that solidified his control over key functions.

‘Broker Butcher’

Authorities are considering reviving the long-disbanded Central Financial Work Commission to allow the ruling Communist Party to assert more control, according to people familiar with the matter.

The commission is set to be headed by Mr Ding Xuexiang, Xi’s chief of staff, one of the people said. Mr He Lifeng, who is expected to become China’s new vice premier, is also being considered for the role of party secretary at the People’s Bank of China, according to the Wall Street Journal.

As part of changing of the guard, the nation’s securities regulator is poised to get a new chairman nicknamed “the broker butcher,” people familiar with the matter said earlier. Mr Wu Qing, a vice mayor of Shanghai, earned his reputation cracking down on wayward traders while at the regulator in the mid-2000s, shuttering 31 firms.

At the same time, the financial industry has been rocked by the disappearance of Mr Bao Fan – who oversaw some of the nation’s biggest tech deals over the past decade.

Mr Bao is cooperating in an unspecified probe by Chinese authorities according to China Renaissance Holdings Ltd., the investment bank he heads up. The Wall Street Journal reported on Thursday that the banker had been detained as part of a corruption probe.

Famed Chinese dealmaker goes missing in latest executive disappearance

Then this week, after an investigation that started last year, China’s top prosecutor charged Mr Tian Huiyu, the former president of China Merchants Bank Co, over allegedly taking “huge” bribes, the abuse of power and insider trading.

That turmoil is giving global investors another reason to be cautious about the longer-term prospects for China’s markets.

The rip-roaring rally on China’s reopening has stalled with key benchmarks in Hong Kong falling as much as 15 per cent since in January. China’s technology stocks have lost up to a combined $263 billion in market value in the same time.

One recent encouraging development – a landmark deal by the US and China to end an impasse over access to audit papers of Chinese firms listed in New York – is also being questioned as authorities in Beijing have put pressure on its state-owned corporate giants to end ties with the Big Four global accounting firms.

“Investors are stuck between a rock and a hard place,” said Ms Diana Choyleva, chief economist at Enodo Economics, a London-based research firm focused on China.

“Liquidity developments favor Chinese equities, but Xi Jinping remains wedded to an economic model which means the Party has ultimate control over every aspect of the economy,” and China remains at risk of falling foul of US sanctions against Russia, she said.

Keeping a tight lid on capital outflows also remains a priority for authorities trying to prevent China’s wealth leaving the country as they get the economy back on its feet.

Beijing has accelerated its crackdown on Macau’s high-rolling gamblers on concerns about the city’s role in funneling money abroad, with the enclave passing a new law that gives the government greater oversight over casinos and authorities jailing flamboyant former industry tycoon Alvin Chau earlier this year.

That effort is shining a spotlight on China’s brokerage industry too. China Securities Regulatory Commission has repeatedly vowed this year to tighten supervision of illegal cross-border brokerage services since it asked two such firms to rectify their business activities.

On top of that, officials have put pressure on foreign and domestic banks to rein in pay in the sector as part of Mr Xi’s “common prosperity” push.

China’s top tech banker is missing? Here’s what that means

Financial Opening

The tightening comes even as authorities have pledged to continue opening up to foreign banks. Wall Street giants such as Goldman Sachs Group Inc and Morgan Stanley, fund managers and insurers are expanding after being allowed to take full control over ventures in China.

The nation has opened its doors in part to attract fresh capital and to instill more discipline in its financial market.

Clean up efforts will proceed as China develops its pension fund system and seeks to draw more liquidity into its markets, according to Mr William Ma, Grow Investment Group’s chief investment officer.

“From a global investors perspective, per our communication with Chinese regulators, there are continued efforts in the financial market opening up,” and more policy announcements are expected after political meetings in March, he said.

One key figure, Mr Guo Shuqing, the party chief of People’s Bank of China and head of the China Banking and Insurance Regulatory Commission, is expected to retire after spearheading a crackdown on leverage in the real estate sector, reining in the shadow banking sector and peer-to-peer lending.

He will leave a big hole to fill as Mr Xi places his associates in key roles, concentrating economic policy decision-making in fewer hands.

“I can’t imagine anyone else has the inclination, reputation, or understanding of the system to replicate what he’s done,” Mr Dinny McMahon, director of markets research at Trivium, said of Mr Guo.

Recent new measures governing bank disclosures of non-performing loans and capital risk may suggest Mr Guo may be trying to ensure his replacement continues to improve risk management, he said.

But it’s a delicate balance for Mr Xi – reducing risks without spooking markets in order to buffer an economy that may yet be subject to more pain as the US and its allies increasingly embrace strategic competition with China.

“Policy makers are attaching great importance to safeguarding the red line and preventing systemic financial risks,” said Mr Shen at Chanson. “It’s particularly crucial at a time when the domestic economy is still suffering and China faces mounting pressure on geopolitical front.”
Posted by at No comments:
Thai opposition party names property tycoon as adviser amid rumours of PM candidacy

MARCH 01, 2023

The Pheu Thai party announced Srettha Thavisin, chief executive of Sansiri, has been brought in as a senior adviser.
Screengrab/Instagram/prestigeth

BANGKOK - Thailand’s biggest opposition party on Wednesday (March 1) named a well-known local property tycoon as its new adviser ahead of an upcoming election, adding fuel to speculation he was being lined up as another prime ministerial candidate.

The Pheu Thai Party, which together with its previous incarnations has won every Thai election since 2001, announced Srettha Thavisin, chief executive of Sansiri, has been brought in as a senior adviser.

“It’s time to do more political work, but let’s take the future step by step,” Srettha, 60, said when asked by reporters about him being a possible candidate for premier, following months of rumours.

Paetongtarn Shinawatra, 36, the Pheu Thai Party's most visible candidate for prime minister, speaks during the general election campaign in Ubon Ratchathani province, Thailand, Feb 17, 2023.
PHOTO: Reuters

Paetongtarn Shinawatra, 36, whose father and aunt led governments overthrown in military coups in 2006 and 2014, has topped opinion polls since 2022 and was confirmed at the weekend as one of Pheu Thai’s prime ministerial candidates.

Under election rules, a party can name up to three candidates for premier.

Pheu Thai has said it would name three.

Srettha said he would be stepping up his presence on the campaign trail for the election, which is due in May.

Read AlsoThailand election likely on May 7, PM Prayut says


“Paetongtarn has done well. But being seven months pregnant, there are limits,” Srettha said.

They will face off against prime minister Prayut Chan-o-cha, a general who led the coup against the last Pheu Thai government in 2014.

Underlining the bitter rivalry between Thailand’s warring political camps, Prayut on Wednesday dismissed questions about Srettha’s prospects and asked reporters what was special about him being a real estate mogul.

“The nation is not a business,” he said, before walking to a waiting car. “Remember my words, the country’s economy is not a family business. Do you understand?”

Source: Reuters

Thaksin's daughter banking on nostalgia to win Thailand election

FEBRUARY 19, 2023

AMNAT CHAROEN – Touting her billionaire family's legacy of populism and massive election victories, Thailand's Paetongtarn Shinawatra is emerging as the candidate to beat in upcoming polls, betting that nostalgia can win millions of working class votes.

Paetongtarn, 36, is campaigning hard in the vote-rich rural strongholds of the Shinawatra family's Pheu Thai political juggernaut, hoping to reignite the kind of fervour that swept father Thaksin and aunt Yingluck to power in unprecedented landslides.

Political neophyte Paetongtarn is promising Pheu Thai will complete unfinished business from three stints in office since 2001, all of which were cut short by court rulings and military coups that it says were orchestrated by Thailand's conservative establishment.

"We managed to fix everything in the first year but then four years later we were ousted by a coup, so there are things that we have not achieved," Paetongtarn told Reuters in her first formal interview with foreign media ahead of the election, expected in May.

"So we go on each stage to tell people how our policies can change their lives. And only through stable politics can people's lives change in a sustainable manner," she said, while campaigning in the northeast.

Thaksin and Yingluck were toppled by the army in 2006 and 2014 respectively, despite overseeing big economic growth. Both live in self-imposed exile to avoid prison convictions that their allies say were designed to prevent their political comebacks.

Old playbook

The baton has passed to Paetongtarn, Thaksin's youngest daughter, who is using the same playbook in offering minimum wage hikes, utilities subsidies and long-promised high-speed rail systems and infrastructure to manage floods and droughts.

Pheu Thai's slogan is Think Big, Act Smart, taking aim at incremental reforms by the military-backed governments of prime minister Prayuth Chan-ocha since he seized power in 2014.

"The picture has to be big, and we must be able to address longstanding problems that festered. These must be completely dealt with," said Paetongtarn.

Though yet to be named as Pheu Thai's prime ministerial candidate, Paetongtarn is far ahead in opinion polls for premier, with twice the support of Prayuth.
Paetongtarn Shinawatra greeting supporters during the general election campaign in Ubon Ratchathani province, Thailand, on Feb 17.
PHOTO: Reuters

Pheu Thai is expected to win most votes, but could struggle to lead a government given the military's influence over an appointed Senate, which, together with the elected lower house, chooses the prime minister.

Paetongtarn said she consults regularly and remains close with her father, who lives mainly in Dubai. His chief worry, she said, was her campaigning while nearly seven months pregnant.

"But I'm OK," she said. "This is my second pregnancy. I am aware of myself. I won't go too hard."

Despite their electoral popularity, the Shinawatras are loathed in Thailand as much as they are loved.

They have long been accused by opponents of cronyism to enrich business friends and of buying off the poor with wasteful populist policies. The Shinawatras deny the charges.
Supporters holding up posters of Paetongtarn Shinawatra during the general election campaign in Amnat Charoen province, Thailand, on Feb 18.
PHOTO: Reuters

Thailand's election is shaping up to be another grudge match between warring elites in Southeast Asia's second-biggest economy.

Paetongtarn said she remains concerned about the impact of the country's intractable power struggle involving her family, including coups, which she said makes Thailand "go backwards".

"It also makes the world see our country in a different light. They don't want to trade with us. It reduces the opportunities for everyone," she said.

"Our country has been frozen for so long. So a coup should not take place again. The country must progress and people deserve to have better livelihoods."
Posted by at No comments:
Development banks must embrace nuclear energy


Håvard Halland
March 02, 2023 




Multilateral development banks (MDBs) have historically been reluctant to invest in nuclear energy, and the World Bank has not financed a nuclear power plant since 1959. In the absence of MDB funds, the majority of international financing for such projects has come from state banks in Russia and China, establishing Russian and Chinese companies as the primary suppliers of nuclear technology to low- and middle-income countries.

While this approach has allowed MDBs to avoid controversy, they must acknowledge that the world has changed. The urgent need to curb greenhouse-gas emissions, together with Russia’s war in Ukraine and subsequent surge in oil and gas prices, has increased global demand for nuclear power. With the 2011 Fukushima disaster fading in the rearview mirror, even Japan is planning to restart its reactors. France, the Netherlands, and the United Kingdom have all announced plans to build new nuclear power plants, Sweden is considering it, and the European Union now allows nuclear energy to be labeled as a green investment. In the United States, the federal government is expected to pump about $40 billion into the sector over the coming decade, and private investment in nuclear energy is surging.

This change in sentiment coincides with rapid technological advances. The development of smaller and safer reactors has made nuclear power cheaper, faster to deploy, and easier to maintain. Whereas the construction of traditional nuclear power plants has historically been a major national undertaking, with costs frequently running into the dozens of billions of dollars, so-called small modular reactors allow for a more tailored approach and more manageable financing packages.

This is particularly important for developing countries, which must figure out how to expand their power supply while curtailing greenhouse-gas emissions as they become increasingly industrialized and urbanized. The International Energy Agency estimates that demand for energy in Africa will jump by one-third by the end of the decade, owing to population and income growth, as well as improved access.

While increased MDB support for renewable energy has helped put developing economies on the path toward carbon neutrality, most countries still rely on coal-fired power plants and natural gas for baseload electricity production. To complete the shift away from fossil fuels, governments must complement wind and solar energy with low-carbon sources that are not dependent on weather conditions.

But without nuclear power (or hydroelectricity, but not all countries have that option), governments will find it difficult to replace their fossil-fuel baseload. While it may be possible to achieve this by combining renewable energy with utility-scale battery storage, the costs are prohibitive, and modern batteries come with their own sustainability issues. Geothermal energy could also play this role, but currently it is limited to areas where geothermal heat is available close to the Earth’s surface. New technologies could expand access to geothermal power, but they are costly.

By abandoning their reticence about nuclear power, MDBs could help scale up low-carbon energy supply while enhancing global security. Western countries’ withdrawal from nuclear energy over the past few decades has enabled Russia to establish itself as the leading international provider of reactors, services, and financing for nuclear-power projects. At a time of heightened geopolitical tensions, it is in the interest of MDBs’ democratic shareholding governments to establish an alternative for emerging countries interested in nuclear power but hesitant to make their energy security dependent on Russia. Simultaneously, MDBs would promote better safety and sustainability standards.

Given that international development agencies tend to follow MDBs’ lead, and that private financing of energy infrastructure projects in developing countries often depends on multilateral lenders’ risk-mitigation policies, MDBs should reverse their position on nuclear power. Otherwise, Russia and China will remain the world’s primary suppliers of such projects.

To be sure, MDBs must carefully assess proposed nuclear energy projects to ensure that they meet appropriate technological and sustainability standards. While some under-resourced countries with weak institutions might not be ready to pursue nuclear power, MDBs are uniquely positioned to support emerging economies seeking alternatives to Russian and Chinese technologies and financing.

The climate crisis, too, has created unprecedented momentum for reform. The US, Germany, a G20 expert panel, and Barbadian Prime Minister Mia Mottley have all called for strengthening MDBs’ capacity to support developing countries in mitigating and adapting to climate change and in mobilizing private financing for this purpose. Meanwhile, the World Bank recently published an “evolution roadmap” that aims to increase its capacity to respond to climate change.

Reforming MDBs’ financing structures and energy policies is crucial to supporting developing countries in mitigating the worst effects of climate change. Moreover, Russia’s war against Ukraine has revealed the critical role of the multilateral financial system as a bulwark against tyranny. Since the start of the war, the World Bank has disbursed $16 billion in financial support to Ukraine, with other multilateral finance institutions providing comparable amounts. By explicitly permitting MDBs to finance nuclear power, their shareholding governments could weaken Russia’s still-considerable influence in emerging countries.

The momentum generated by nuclear energy’s renaissance, the geostrategic imperative to reduce Russia’s role as the dominant international provider of nuclear energy infrastructure, and the looming climate crisis, has presented MDBs with a unique opportunity to update their nuclear energy policy. To fight climate change and achieve a safer, more sustainable future, they must seize it.

The opinions and arguments expressed here are those of the authors and do not necessarily reflect the official views of the OECD or its member countries.

Co-author: Jessica Lovering is Executive Director of the Good Energy Collective

Copyright: Project Syndicate


-- Contact us at english@hkej.com

Posted by at No comments:
Subscribe to: Posts (Atom)