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Monday, February 13, 2023

Tight job market? AI meets worker shortage

FILE PHOTO-OpenAI and ChatGPT logos are seen in this illustration taken, February 3, 2023. REUTERS/Dado Ruvic/Illustration

THE two investment obsessions of the year so far – artificial intelligence (AI) and super-tight labour markets – meet head on.

If the hype about the former is to be believed, concern about the inflationary impact of the latter should be well wide of the mark. If only they were so perfectly aligned.

Timing is everything of course. The speed with which ChatGPT-style AI tools zap swathes of white-collar desk jobs could be more glacial than any Big Tech rah-rah suggests – and at least slower than the 12-18 months of the Federal Reserve’s current policy horizon.

But two reasonable questions are being asked around investment houses.

Does the wave of layoffs in the digital and banking worlds this year relate directly to the presumed quantum leap in so-called generative AI – just as pandemic-related overstaffing and more recent job hoarding is being pared back?

And if it does, should policymakers relax more about what could be temporary worker shortages in the service sector, where most of the wage and inflation concerns seem to centre?

Far from relaxing, should office or home-based workers now fret that we’re in for anything but a tight jobs market over the coming years?

More questions than answers perhaps – but enough to have investment strategists thinking laterally and joining dots.

Morgan Stanley’s thematic research team said last week it was inundated with enquiries about generative AI during its recent client visits.

And while investment fads come and go, they said, this one is “worth considering seriously” given the speed of take-up and its diffusion across many industries.

Aside from stock price and valuation frenzies, the team said a new wave of AI fed the debate about white-collar industry disruption in a “creative destruction moment” – with possible side benefits from reskilling workers to better wage diffusion.

Citing numbers indicating employment in business, knowledge, customer and developer outsourcing in excess of 100 million across Asia alone, Morgan Stanley said the impact was already being felt even if the jury was still out on “the degree to which it is deflationary or productivity enhancing.”

If this generative AI takes the tech transformation to non-routine office work that it largely skirted over the last decade, it will affect tens of millions more jobs than currently assumed.

The two sides of the theoretical debate at least are whether that then leads to mass unemployment and demand problems – requiring a reconsideration of things like universal basic income to support economies – or whether productivity gains lift wages and see workers simply choosing to work ever fewer hours over time as bots take their place.

London-based Fathom Consulting last Thursday concluded that a “fourth industrial revolution powered by AI could greatly affect the demand for and supply of labour” and the United States and China were bound to vie for leadership.

“The speed and impact of this change will be profoundly disruptive for global politics and for the structure of the labour market,” economists Erik Britton and Andrew Harris wrote, adding that the United States needed to keep investing in tech that both supports and replaces labour in order to retain its edge.

But just what is the scale of the likely disruption?

A frequently cited study by business consultant McKinsey from 2017 showed 60% of occupations worldwide have at least 30% of work activities that could be automated – even though automation may well create more jobs in tandem.

That tallies with numbers from the Organisation for Economic Cooperation and Development, which reckoned 10% to 15% of jobs will be lost due to tech changes over the next 20 years – but about as many may be created in other industries.

While varying hugely among the 46 countries it examined, the McKinsey study said up to 30% of activities could be displaced by 2030 – with advanced and ageing economies more likely to move faster given higher wages and incentives.

More recent polling from McKinsey last year showed companies saying at least a quarter of their tasks could be automated over the next five years but less than a fifth of respondents reckoned their firms were yet in a position to do that.

And that observation underlines the timing of all this in terms of years. How soon do tech revolutions change the world – and at least aggregate demand or supply for workers?

As the flub by Alphabet’s chatbot Bard illustrated in spectacular fashion this week, the big problem for the latest wave of emerging AI is still one of accuracy.

“While ChatGPT’s output is credible, accuracy is its Achilles’ Heel,” Morgan Stanley’s team wrote. “Manual validation should act as a breakwater to this employment threat for now.”

If creases take years to iron out, perhaps it’s not so useful to see the craze providing a timely offset to tight labour markets and wage inflation.

There’s even a chance the trepidation may exaggerate the prevailing conundrum and cause as many problems as the reality.

In a discussion paper published by the Centre for Economic Policy Research last month, economists Marta Golin and Christopher Rauh said their work found a “strong relationship” between worry about automation and intentions to join a union, retrain or switch occupations, preference for taxation and government handouts, populist attitudes and voting intentions.

Much like the pandemic, fear of automation could have as big an economic impact as its actual spread. — Reuters

Mike Dolan is a columnist for Reuters. The views expressed here are the writer’s own. 

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Tight jobs market? AI meets worker shortage :Mike Dolan


LINKEDIN EMPOWERS MALAYSIA’S TOP EMPLOYERS

To assist companies in charting effective talent management strategies, LinkedIn, Shahul, Yee and edotco Group chief people officer Ramon Chelva will share insights in a panel on Feb 21, 2023.

Information and registration here: https://events.thestar.com.my/event/the-talent-magnet-how-to-build-a-thriving-workforce/

 

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   ChatGPT may have blown away many who have asked questions of it, but scientists are far less enthusiastic. Lacking data privacy, wrong .

Lies, racism and AI: IT experts point to serious flaws in ChatGPT

 


 ChatGPT may have blown away many who have asked questions of it, but scientists are far less enthusiastic. Lacking data privacy, wrong information and an apparent built-in racism are just a few of the concerns some experts have with the latest 'breakthrough' in AI. — Photo: Frank Rumpenhorst/dpa

BERLIN: ChatGPT may have blown away many who have asked questions of it, but scientists are far less enthusiastic. Lacking data privacy, wrong information and an apparent built-in racism are just a few of the concerns some experts have with the latest 'breakthrough' in AI.

With great precision, it can create speeches and tell stories – and in just a matter of seconds. The AI software ChatGPT introduced late last year by the US company OpenAI is arguably today's number-one worldwide IT topic.

But the language bot, into which untold masses of data have been fed, is not only an object of amazement, but also some scepticism.

Scientists and AI experts have been taking a close look at ChatGPT, and have begun issuing warnings about major issues – data protection, data security flaws, hate speech, fake news.

"At the moment, there's all this hype," commented Ruth Stock-Homburg, founder of Germany's Leap in Time Lab research centre and a Darmstadt Technical University business administration professor. "I have the feeling that this system is scarcely being looked at critically."

"You can manipulate this system"

ChatGPT has a very broad range of applications. In a kind of chat field a user can, among others, ask it questions and receive answers. Task assignments are also possible – for example on the basis of some fundamental information ChatGPT can write a letter or even an essay.

In a project conducted together with the Darmstadt Technical University, the Leap in Time Lab spent seven weeks sending thousands of queries to the system to ferret out any possible weak points. "You can manipulate this system," Stock-Homburg says.

In a recent presentation, doctoral candidate and AI language expert Sven Schultze highlighted the weak points of the text bot. Alongside a penchant for racist expressions, it has an approach to sourcing information that is either erroneous or non-existent, Schultze says. A question posed about climate change produced a link to an internet page about diabetes.

"As a general rule the case is that the sources and/or the scientific studies do not even exist," he said. The software is based on data from the year 2021. Accordingly, it identifies world leaders from then and does not know about the war in Ukraine.

"It can then also happen that it simply lies or, for very specialised topics, invents information," Schultze said.

Sources are not simple to trace

He noted for example that with direct questions containing criminal content there do exist security instructions and mechanisms. "But with a few tricks you can circumvent the AI and security instructions," Schultze said.

With another approach, you can get the software to show how to generate fraudulent emails. It will also immediately explain three ways that scammers use the so-called "grandchild trick" on older people.

ChatGPT also can provide a how-to for breaking into a home, with the helpful advice that if you bump into the owner you can use weapons or physical force on them.

Ute Schmid, Chair of Cognitive Systems at the Otto Friedrich University in Bamberg, says that above all the challenge is that we can't find out how the AI reaches its conclusions. "A deeper problem with the GPT3 model lies in the fact that it is not possible to trace when and how which sources made their way into the respective statements," she said.

Despite such grave shortcomings, Schmidt still argues that the focus should not just concern the mistakes or possible misuse of the new system, the latter prospect being students having their homework or research papers written by the software. "Rather, I think that we should ask ourselves, what chances are presented us with such AI systems?"

Researchers in general advocate how AI can expand – possibly even promote – our competencies, and not limit them. "This means that in the area of education I must also ask myself – as perhaps was the case 30 years ago with pocket calculators – how can I shape education with AI systems like ChatGPT?"

Data privacy concerns

All the same, concerns remain about data security and protecting data. "What can be said is that ChatGPT takes in a variety of data from the user, stores and processes it and then at a given time trains this model accordingly," says Christian Holthaus, a certified data protection expert in Frankfurt. The problem is that all the servers are located in the United States.

"This is the actual problem – if you do not succeed in establishing this technology in Europe, or to have your own," Holthaus said. In the foreseeable future there will be no data protection-compliant solution. Adds Stock-Homburg about European Union data protection regulations: "This system here is regarded as rather critical."

ChatGPT was developed by OpenAI, one of the leading AI firms in the US. Software giant Microsoft invested US$1bil (RM4.25bil) in the company back in 2019 and recently announced plans to pump further billions into it. The concern aims to make ChatGPT available to users of its own cloud service Azure and the Microsoft Office package.

"Still an immature system"

Stock-Homburg says that at the moment ChatGPT is more for private users to toy around with – and by no means something for the business sector or security-relevant areas. "We have no idea how we should be deal with this as yet still immature system," she said.

Oliver Brock, Professor of Robotics and Biology Laboratory at the Technical University Berlin, sees no "breakthrough" yet in AI research. Firstly, development of AI does not go by leaps and bounds, but is a continuing process. Secondly, the project only represents a small part of AI research.

But ChatGPT might be regarded as a breakthrough in another area – the interface between humans and the internet. "The way in which, with a great deal of computing effort, these huge amounts of data from the internet are made accessible to a broad public intuitively and in natural language can be called a breakthrough," says Brock. – dpa    

By Oliver Pietschmann, Christoph Dernbach

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Sunday, February 12, 2023

OUR MANY APPETITES: Figuring out the right amount of protein we need could be the key to weight management

People follow various diet fads, hoping to unlock the secret to weight management. — Photos:123rf.com 

This dia­gram indic­ates the out­come of a diet­ary “chase” (res­ult­ing in the “excess Cal­or­ies”) from an ini­tial inad­equate to a more optimal level of pro­tein con­sump­tion.

 

How much pro­tein a per­son needs depends on his life­style too. - 123rf.com
 


Figuring out the right amount of protein we need could be the key to weight management.

MANY would have enjoyed the 15-day Chinese New Year season of bingeing on food and drink, and some would have added on a few spare kilos of weight as a result. My own Body Mass Index (BMI) is heading back towards 27 (again) which means I am significantly overweight (again) and this simply implies some immediate weight loss is needed.

At my advanced age, being overweight confers no momentous benefits, but can present several potential negatives, so weight control in such circumstances is quite important. And this is why a 2013 published study into a single wild female Chacma baboon named Stella in South Africa may be relevant.

Researchers from various anthropological and veterinary science institutes embarked on analysing in detail the food consumption of Stella over a 30-day window, breaking down her diet into the three macronutrients: carbohydrates, fats and proteins.

The study was done in South Africa in a region where there was a diverse range of foods available for baboons, and the original purpose was to establish if baboons can (a) regulate their intake of macronutrients, (b) cope with dietary restrictions, and, (c) establish a timescale for nutritional demands.

The data surprisingly indicated that Stella’s diet was driven primarily by the amount of protein eaten. Regardless of food availability, the ratio of calories from non-protein energy to energy from proteins was remarkably steady at 5:1, and this ratio was maintained every day. The wet mass of food varied considerably with an average of 1.9 kilos a day, and may fluctuate by 800 grams daily.

Stella’s average daily calorie intake was 940 calories, which varied up or down by 426 calories a day. The study found that the other two macronutrients, fats and carbohydrates were interchangeable with each other as far as Stella was concerned, and the overriding driver of total calories consumption was solely the amount of protein in Stella’s diet.

Protein leverage


The astonishing outcome of the study on Stella was actually predicted much earlier, by two Australian researchers, Simpson and Raubenheimer, in their 2005 paper, ‘Obesity: the protein leverage hypothesis’ where a simple mathematical model was presented which offered a plausible explanation for the global human obesity epidemic.

Summarised, the Protein Leverage Hypotheses (PLH) is simple. Like baboons, people eat to satisfy their need for protein, and they will eat potentially enormous amount of carbohydrates and fats until the food

eaten finally fulfills their protein requirement. And if people do not get enough protein, then they will simply eat more and more foods (which often contain carbohydrates and fats) in a forlorn quest for protein.

The body’s need for a relatively small amount of protein can therefore hugely “leverage” the consumption of other foods. And as such other foods contain more calories than proteins, the final result is often the accumulation of body fats resulting in obesity.

The obvious and significant difference between Stella and humans is that baboons appear able to restrict the overconsumption of fats and carbohydrates, even in the absence of protein. There may be several reasons for this. Perhaps there is a “protein switch” in baboons, or more probably, the range of foods available for baboons is simply limited, unlike for most humans.

Modern food production techniques use all sort of chemicals and flavouring compounds to mimic the texture and taste of protein-rich foods, resulting in processed foods that taste remarkably like proteins, but actually have very little or zero protein content. These foods have lots of cheap carbohydrates and fats instead, as protein is an expensive ingredient to include in processed foods.

Classic example are potato-based snacks and crisps, which come in all sorts of “meaty” flavours, even though there is usually no meat or protein content. According to the PLH, humans can easily consume many thousands of calories from meat-flavoured crisps in a futile attempt to satisfy the need for protein. Their taste senses will be fooled into erroneously provoking the consumption of such fake foods.

The amount of proteins needed by humans vary with age, with older people needing more protein content in their diets. And this includes both vegetable-based and animal sources of protein as there is little difference in the way the body processes proteins in general. Proteins are linkages of amino acids which the body disassemble into various smaller amino acids and molecules and recombine into other compounds to create enzymes, hormones and other tissues.

The main differences between animal and vegetable proteins are that meat proteins are considered “complete” proteins as they contain all 9 of the essential amino acids, and additionally they have some micronutrients (eg, certain minerals) which may not be present in plant proteins. However, these variances are easily resolved by adding or cooking/preparation with various added ingredients.

Our five appetites?

Leading from the PLH, where it seems that baboons and humans can detect the protein content of food, Simpson and Raubenheimer further proposed a theory that humans may actually have five different appetites, one each for protein, fat, carbohydrate, calcium and salt. Note that these are appetites which may reflect a physical need and not the same as taste sensors in the mouth, which are reflective of eating pleasures and displeasures.

There may be an element of truth involved, though the science is still unclear. Certainly, salt and some carbohydrates such as sugar can be detected by taste buds in the mouth. Fats can apparently be detected by specialised sensors in human digestive tracts, calcium may be detectable via a protein known as NCS-1 encoded by the FREQ gene in humans, and the real puzzle is how humans can detect proteins in the diet. Some papers have suggested that humans may have amino acid chemoreceptors, but it is far from clear that these receptors are involved in creating an “appetite” for protein as there are no neural linkages associated with these receptors.

Therefore, it is plausible that proteins are complex foods which require more processing for digestion and hence the lack of protein may be inferred by the body from the lack of digestive effort (and continued feeling of hunger) when insufficient protein has been ingested. We do not know for certain, even though the effect of humans eating inadequate amounts of proteins appears to be observable.

Regardless, of all the five appetites proposed, by far the most dominant appetite is for protein. The other may be in place to remind the body to also consume other macro- and micro-nutrients.

Too much protein is bad too

However, too much dietary protein can also be bad. The muchhyped keto diet is basically a meal plan comprising of primarily proteins and fats, which is quite odd, if one thinks about it.

Here is some simple maths. A gram of fat contains nine calories, a gram of sugar (carbohydrate) contains 4 calories, and protein is roughly the same as sugar. So if one wants to lose weight, it would make sense to ingest only proteins and carbohydrates, and skip the fats. However, the inclusion of carbohydrates would preclude the onset of ketosis, which is the phase when the body begins to burn stored body fat, instead of deriving energy from the carbohydrates.

This may be good for short-term weight loss, but it is also likely to have an effect on the kidneys because any diet too high in protein ends up building acid in the bodily fluids. This causes the kidneys to excrete the excess acid which is extracted using the calcium from the bones, resulting in excessive calcium loss.

The kidneys themselves may be damaged, especially if there is not enough water in the diet. There are also other side effects which can impact the liver and the heart, but it seems that the keto diet can work with healthy, younger adults, though it is probably less suitable for older people.

The right amount

Although it is a subjective matter, the amount of protein needed daily generally depends on physical activity and age. For a healthy adult, the minimum requirement is 0.8 grams per kilo of weight. So an adult weighing 70 kilos would need a minimum of 56 grams of protein daily. For younger, growing people and people who are more active, the requirement rises to 1 gram to 1.6 grams per kilo of body weight.

Older people, aged 65 or more, generally require around 50% more protein than someone younger, so an inactive pensioner should aim for 1.2 grams of protein per kilo of body weight, rising to perhaps 2 grams per kilo for a reasonably active pensioner.

Translated into food, 56 grams of protein is obtainable from around 200 to 250 grams of meat or fish, or 160 grams of dry soybeans.

Once the daily protein requirement is established, aim to consume the right amount of protein daily and vary the calories from the rest of food to a point where one feels comfortable, especially if the target is weight loss. One can also increase the daily protein amounts if hunger pangs persist. Cravings for overeating should be reduced once the right amount of protein has been found, according to the PLH. 

 


By  Curious cook CHRIS Chan - The views expressed here are entirely the writer’s own. 

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How Much Protein Do You Need to Eat Per Day to Lose Weight?

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Saturday, February 11, 2023

Demystifying the property market overhang


AN account­ant, who is tasked with pre­par­ing the books of a cor­por­ate, will always be guided by account­ing prin­ciples when it comes to how the fin­an­cial state­ments of the com­pany are presen­ted on an annual basis to ensure they are accur­ate and reflect­ive of the com­pany’s busi­ness affairs.

An aud­itor, look­ing at the same pre­pared accounts, will run through the num­bers and audit the key mater­ial items to ensure they are reas­on­able, reflect­ive of the com­pany’s fin­ances, and free from mater­ial mis­state­ments, includ­ing due to fraud or error, or applic­a­tion of wrong account­ing treat­ment.

In fin­an­cial state­ments, two of the most crit­ical items are receiv­ables and invent­or­ies.

In order to have proper account­ing treat­ment, account­ants and aud­it­ors used account­ing the­or­ies to describe what is deemed to be cur­rent, and those that have a longer-dated age­ing pro­file are either impaired or writ­ten off.

The reason for this is to ensure that the fin­an­cial state­ments reflect the status of a cor­por­a­tion’s cur­rent assets and are in no way doubt­ful.

There is also an applic­a­tion of gen­eral pro­vi­sion or spe­cific pro­vi­sion when it comes to how these bal­ances ought to be treated in the fin­an­cial state­ments.

Often, we see cases of over-inflated bal­ances and when it came to the crunch of the mat­ter, the man­age­ment would have no choice but to write them off.

The ‘real’ over­hang

At the recently con­cluded 15th Malay­sian Prop­erty Sum­mit 2023, the Dir­ector of the National Prop­erty Inform­a­tion Centre (Napic) presen­ted a paper on the status of the Malay­sian prop­erty mar­ket up to the third quarter of last year (3Q22), with some data points related to the per­form­ance of the mar­ket up to Novem­ber 2022.

The full mar­ket report is only expec­ted to be released in the middle of next month, where Napic will not only provide the usual annual update of the mar­ket’s per­form­ance but also provide more insight into some of the key data points that have been much dis­cussed among all stake­hold­ers, of which, one of them is the status of over­hang in the mar­ket.

As we are aware, the res­id­en­tial over­hang at the end of 3Q22 stood at 29,535 units worth some Rm19.95bil.

Napic’s web­site also provided the details of where these over­hang prop­er­ties are loc­ated and the three key states – Johor, Selangor, and Pen­ang – are the main hot­spots, account­ing for some 14,956 units or just over half of the coun­try’s total over­hang.

In terms of the type of prop­er­ties, the 3Q22 data showed that high-rises com­prise 18,962 units or 64.2% of the total over­hang.

In terms of price points, 23.8% of the total over­hang was priced at RM300,000 and below, 29.5% was priced between RM300,001 and RM500,000, 31.6% was priced between RM500,001 and Rm1mil and the bal­ance was priced above Rm1mil.

In terms of the total value, the res­id­en­tial over­hang is skewed towards the high-end seg­ment with prop­er­ties worth more than Rm1mil account­ing for 43.4% of the total over­hang value, while those priced between RM500,001 and Rm1mil accoun­ted for 31.9% of the total over­hang.

Prop­er­ties priced between RM301,000 and RM500,000 have a total over­hang value of just Rm3.5bil, while prop­er­ties priced below RM300,000 are worth some Rm1.39bil. These two rep­res­ent some 24.8% of the total over­hang value.

For the ser­vice apart­ments, the total over­hang in units stood at 23,688 worth some Rm20.21bil as at end of 3Q22, with Johor alone account­ing for 62.4% of the total.

Most of these over­hangs in the seg­ment are prop­er­ties priced between RM500,001 and Rm1mil, which accoun­ted for two-thirds of the total unit num­bers and 58.9% in value of the total over­hang.

For the longest time, Napic had not shared with the stake­hold­ers the key under­ly­ing age­ing pro­file of this over­hang, and that has led to a mis­lead­ing status of the mar­ket’s over­hang status. It was indeed an eye-opener to see what the real over­hang has been.

For example, as seen in Table 1, the key over­hang is prop­er­ties (both res­id­en­tial and ser­vice apart­ments across the four key states) that have been part of the stat­ist­ics for the last five years and they account for between 51% and 93% of the total over­hang units.

For example, as seen in Table 1, the key over­hang is prop­er­ties (both res­id­en­tial and ser­vice apart­ments across the four key states) that have been part of the stat­ist­ics for the last five years and they account for between 51% and 93% of the total over­hang units.

In total, these prop­er­ties accoun­ted for a whop­ping 75.7% of the mar­ket’s over­hang status while prop­er­ties that have been in the mar­ket for the last three years are just over 5% from the key states.

Spe­cific men­tion must also be made on ser­vice apart­ments loc­ated in Johor, and those that are in the five to 10 years bucket, as they account for 26% of the total mar­ket over­hang.

In terms of prices, most of the over­hang is seen in the same five to 10 years bucket across the board and they alone account for 71% of the total over­hang prop­er­ties in the mar­ket.

As seen in Table 2, prop­er­ties below three years account for less than 5% of the total mar­ket over­hang. Spe­cific men­tion must also be made on ser­vice apart­ments that are in the RM500,001 to Rm1mil bracket and are in the five to 10 years bucket as they account for 25% of the total mar­ket over­hang.

In the cor­por­ate world, when one is up against data that is dis­tort­ing the real pic­ture, the proper thing to do is to see whether the data is still rel­ev­ant or oth­er­wise.

Clearly, look­ing at the age­ing pro­file of the prop­erty over­hang, those above five years will likely remain unsold for a fore­see­able future, mainly due to either being wrongly loc­ated and without the proper or good infra­struc­ture to sup­port com­munity liv­ing, or untouched by prop­erty buy­ers for simply being too expens­ive, espe­cially those bey­ond the RM500,000 price threshold.

Clearly, look­ing at the age­ing pro­file of the prop­erty over­hang, those above five years will likely remain unsold for a fore­see­able future, mainly due to either being wrongly loc­ated and without the proper or good infra­struc­ture to sup­port com­munity liv­ing, or untouched by prop­erty buy­ers for simply being too expens­ive, espe­cially those bey­ond the RM500,000 price threshold.

Hav­ing iden­ti­fied the issues, reg­u­lat­ors and prop­erty developers would need to come out with strategies to address them and to attract buy­ers to these prop­er­ties via a rehab­il­it­a­tion exer­cise and with a sig­ni­fic­ant price reduc­tion.

The bot­tom line is to remove them from the over­hang data.

Let’s call a spade a spade

So what is Malay­sia’s real over­hang? Based on the data presen­ted by Napic, one can take com­fort that over­hang is not as ser­i­ous as it is made out to be mainly due to a lack of data and proper ana­lysis in terms of what is real over­hang pre­vi­ously.

While those more than three years but less than five years are part of stat­ist­ics, we should redefine them as core over­hang while those bey­ond five years can be redefined as hard­core over­hang.

As we have been able to slice and dice these num­bers, the real over­hang is only per­haps less than 5% of the mar­ket in terms of the num­ber of units and value.

Napic could also help stake­hold­ers to under­stand bet­ter the prop­erty mar­ket data bet­ter by break­ing down the data points as an over­hang that is mainly due to gov­ern­ment hous­ing schemes and those that are privately built.

In this way, we could also see whether the gov­ern­ment’s inter­ven­tion is needed to boost demand for these obscurely loc­ated prop­er­ties.

For the private developers, most of these invent­or­ies would have been impaired as the like­li­hood of the assets being real­ised in full value or even at 50% to 60% of the mar­ket value is seen as low.

Private developers too ought to think out­side of the box on how to over­come the prop­erty invent­or­ies sit­ting in their books as being part of the stat­ist­ics only res­ults in paint­ing the wrong pic­ture for the prop­erty mar­ket as a whole.

By Pankaj C. kumar is a long-time invest­ment ana­lyst. the views expressed here are the writer’s own. 

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ChatGPT And The Future Of AI, Turkey Earthquakes.Part 1

 


How Scientists Predict Where Earthquakes Will Strike Next

The pair of earthquakes that hit Turkey and Syria this week left the region grappling with death and destruction. Despite the region being seismically active, this particular area hadn’t seen an earthquake of this size for decades. There are ways of knowing where the next big earthquakes will happen. —but not when. Scientists use knowledge of fault lines and historical data to make their predictions, but saving areas from mass casualties often relies on infrastructure policies. Building codes that prioritize strong buildings can save lives, but older structures remain vulnerable.

Across the globe, in California, the health impacts of electric vehicles are beginning to be seen. A study published this month finds that for every 20 EVs in a zip code, asthma-related visits to the emergency room drop by 3.2%. This is a striking number for a technology that’s just now becoming more commonplace. Joining Ira to talk about these stories and more is Umair Irfan, staff writer at Vox, based in Washington, D.C. 

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ChatGPT And Beyond: What’s Behind The AI Boom?

The past few months have seen a flurry of new, easy-to-use tools driven by artificial intelligence. It’s getting harder to tell what’s been created by a human: Programs like ChatGPT can construct believable written text, apps like Lensa can generate stylized avatars, while other developments can make pretty believable audio and video deep fakes.

Just this week, Google unveiled a new AI-driven chatbot called Bard, and Microsoft announced plans to incorporate ChatGPT within their search engine Bing.  What is this new generation of AI good at, and where does it fall short?

Ira talks about the state of generative AI and takes listener calls with Dr. Melanie Mitchell, professor at the Santa Fe Institute and author of the book, Artificial Intelligence: A Guide for Thinking Humans. They are joined by Dr. Rumman Chowdhury, founder and CEO of Parity Consulting and responsible AI fellow at the Berkman Klein Center at Harvard University. 

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ranscripts for each segment will be available the week after the show airs on sciencefriday.com.

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 Rrlated:

ChatGPT, the future of AI

 7 problems facing Bing, Bard, and the future of AI search

 

 

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