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China’s Moonshot AI stole from Anthropic, Trump tech adviser says

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Visitors at a trade show in Shanghai visit a booth with the Kimi sign displayed in large block letters

A White House adviser has accused China’s Moonshot AI of a “large scale” effort to steal the capabilities of top US artificial intelligence (AI) models.

US President Donald Trump’s Science and Technology adviser Michael Kratsios said Moonshot AI carried out the campaign through what is known as distillation – when a weaker AI model extracts answers from a stronger one.

Moonshot also gained access to restricted cutting-edge Nvidia servers to train its models, Kratsios said in a social post, external on Wednesday.

The BBC has contacted Moonshot, Anthropic, the White House and Nvidia for comment.

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Kratsios said on X that the US government has information that Moonshot AI “distilled” capabilities from Anthropic’s Fable AI for the development of its K3 model.

Kimi K3 gained attention around the world after it was unveiled last week, with many believing it to have narrowed the gap between Western and Chinese AI models. Moonshot said its K3 model is able to rival top US technology.

Kratsios’ allegations come just a day after Treasury Secretary Scott Bessent said the US would examine whether Chinese AI models have stolen the capabilities from American rivals.

“We’ve seen a lot of talk about open-source models coming and threatening the large language models in the US,” Bessent told Fox Business on Tuesday.

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“If we see, especially, that overseas models are stealing from our great companies, we have the ability to sanction them,” he added.

The increased scrutiny by the US of Chinese AI companies also comes as Trump is expected to meet his Chinese counterpart Xi Jinping in September.

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Microsoft: A Better Entry Point Before Earnings

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Microsoft: A Better Entry Point Before Earnings

Microsoft: A Better Entry Point Before Earnings

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Lotus announces balance sheet reset

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Lotus announces balance sheet reset

Lotus Resources has announced a series of measures to reset its balance sheet, as it aims for steady-state production at its Kayelekera project in Malawi.

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Greg Poland’s lawyer Martin Bennett doubts ‘secret’ tape authenticity in defamation trial

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Greg Poland’s lawyer Martin Bennett doubts ‘secret’ tape authenticity in defamation trial

Businessman Greg Poland’s lawyer, Martin Bennett, has questioned the authenticity of a 46-minute recording at the centre of a defamation trial against former journalists and Canning MP Andrew Hastie.

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Asia FX: Yen steadies near 40-year low; won hits 2-1/2 month high

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Asia FX: Yen steadies near 40-year low; won hits 2-1/2 month high

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Dr Reddy’s shares crack 9% after weak Q1; these 3 brokerages slash their target prices

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Dr Reddy’s shares crack 9% after weak Q1; these 3 brokerages slash their target prices
Shares of Dr Reddy’s tanked 9% to Rs 1,080 on the BSE on Thursday after the company announced a weak set of numbers with profitability and revenue both dipping in the first quarter of the financial year 2027.

The company’s net profit was Rs 443 crore, marking a sharp 69% plunge for the quarter under review, while revenue from operations stood at Rs 8,071 crore, a 6% decline from the corresponding quarter of the previous financial year.

Dr Reddy’s said that the company faced a semaglutide API-related impact of Rs 240 crore, including inventory provisions and other associated costs. EBITDA margin was further affected by higher solvent and freight costs arising from the Middle East conflict. Reported RoCE stood at 5.3%, while RoCE excluding the semaglutide API impact was 8%. The company had a net cash surplus of Rs 3,058 crore.

Also read: Dr Reddy’s aims to resume semaglutide supply by November after API fix

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Should you sell Dr Reddy’s shares?

Motilal Oswal maintained its Neutral rating on Dr Reddy’s with a target price of Rs 1,121, implying 5% downside. The brokerage cut its earnings estimates by 2% for FY27 and 3% for FY28, factoring in higher operating expenses due to the Middle East conflict and moderate growth in the PSAI segment.
It expects earnings to decline in FY27 and recover from FY28, given the ongoing work to resolve the Semaglutide-related regulatory issue, commercial benefits from b-abatacept expected from 4QFY27 onward and a high FY26 base. Motilal Oswal values Dr Reddy’s at 20x 12-month forward earnings and said its Neutral stance reflects the company’s earnings trajectory and current valuations.


Systematix maintained its Hold rating on Dr Reddy’s with a target price of Rs 1,183, saying the quarter was materially weaker than expected. North America revenue was significantly below estimates as the company recorded no generic semaglutide supplies during the quarter, while all other business segments performed broadly in line with expectations. Adjusted for one-offs and including other income, EBITDA stood at Rs 10.9 billion, with a 13.5% margin, which was meaningfully below the brokerage’s expectations.
Read more: Dr Reddy’s flags quality issue in semaglutide batches, delays commercial supplies
Dolat Capital downgraded Dr Reddy’s to Reduce from Buy and revised its target price to Rs 1,246, implying 5% downside, after Q1FY27 earnings came in below estimates even after adjusting for the Semaglutide-related inventory provision. The brokerage said the base business margin was lower than expected. Dolat Capital cut its FY27E and FY28E EPS estimates by 25.7% and 18%, respectively, factoring in lower Semaglutide sales, with management guiding for 6-7 million pens compared with 12 million earlier, along with lower-than-expected base business margins. The revised target price is based on 23x FY28E EPS.
During the quarter, the company received a Form 483 with seven observations following a pre-approval inspection at its biologics facility in Bachupally in June 2026 and responded within the stipulated timeline. It also said certain batches of Semaglutide were found to be out of specification due to an issue associated with the API.

(Disclaimer: Recommendations, suggestions, views and opinions given by the experts are their own. These do not represent the views of The Economic Times)

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BOJ to raise rates again by December as weak yen revives inflation risks: Reuters poll

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BOJ to raise rates again by December as weak yen revives inflation risks: Reuters poll

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Now Listen PR Reveals Why Independent Artists Are Adopting Startup Strategies

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Spotify

For a long time, music marketing was mostly instinct.

Artists released tracks, sent them to blogs, hired PR teams, posted on social media and hoped something would connect. Sometimes it did. Often it didn’t. Much of the industry operated on gut feeling rather than anything measurable, and the results reflected that inconsistency.

That has changed and quite fundamentally so.

Data has quietly reshaped almost every part of how music is promoted. Whether artists are aware of it or not, numbers now influence everything from release schedules to TikTok strategy to which songs a label decides to push hardest.

There is a reasonable concern that this makes music feel clinical – that creativity is being reduced to audience graphs and retention curves. It is a fair observation. But it misses the broader point.

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Good data does not replace creative instinct. It gives artists and their teams a clearer picture of what is resonating and why, which in most cases makes the creative decisions sharper, not more formulaic.

The Industry Has Moved Beyond Streams

Streams are still part of the conversation, but they have become almost a baseline metric. What the industry pays closer attention to now are the behavioural signals that sit beneath them.

  • Are listeners saving the track?
  • Are they returning to replay it?
  • At what point are they dropping off?
  • Which clips are being watched through to the end?

Those details tell a considerably more meaningful story than raw play counts ever could.

A track with 20,000 streams but a high save rate will often attract more internal attention than one with inflated plays and no meaningful engagement. Labels monitor this closely, as do managers, PR teams and playlist curators.

The reasoning isn’t complicated: inflated play counts are relatively easy to manufacture. Genuine listening behaviour is considerably harder to replicate artificially and the industry has become sophisticated enough to tell the difference.

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TikTok Changed the Entire Marketing Cycle

Before short-form platforms reshaped consumption habits, releases followed a relatively linear path. Tease the single, release it, push for press coverage, then move on to the next project.

The process is now considerably less predictable and in many respects more interesting for it.

Tracks can gain significant traction months, or even years after their original release date because a single clip connects with the right audience at the right moment. Doechii’s “Anxiety” is a notable example. Originally recorded as a demo in 2019, it was rediscovered by the TikTok community in early 2025, which prompted Doechii to re-record and officially release it. The track went on to generate 51.6 billion views and was named TikTok’s Music Trend of the Year – reaching #3 in the UK singles chart and earning five Grammy nominations in the process.

Artists are now making decisions about which songs become singles based on how audiences respond online. Some are even revisiting arrangements after previewing snippets and observing the reaction data.

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A few years ago, that would have seemed far-fetched. Now it’s simply part of how the industry operates.

Many artists still resist the idea because they associate “data-driven” with trend-chasing or engineering music to suit an algorithm. In practice, it is rarely that reductive. Most of the time, it simply means paying closer attention to what audiences are already communicating through their listening behaviour.

If thousands of people are returning to a specific moment in a track, that pattern is worth understanding.

Why the Smartest Campaigns Start With Data

One of the most significant differences between emerging artists and established teams now is access to information and the ability to act on it intelligently.

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The artists growing most consistently tend to have a clear understanding of:

  • Where listeners are discovering them
  • Which content formats are converting most effectively
  • When their audience is most likely to engage
  • Which songs are sustaining attention over time

This isn’t about being obsessed with analytics. It’s about avoiding the kind of wasted energy that undermines otherwise strong campaigns.

Investing weeks into a platform that is not converting is a drain on both budget and momentum. Assuming that every audience behaves in the same way leads to campaigns that fail to connect with anyone in particular.

An independent band building an audience through vinyl collectors will approach marketing very differently to a rap artist growing through TikTok edits and fan-driven content. The data makes that distinction clear relatively quickly, and the campaigns that ignore it tend to show it.

Even PR Has Become More Measurable

This is perhaps one of the most significant structural shifts the industry has seen in recent years.

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PR has historically been difficult to track with any real precision. Coverage would land, streams might see a short-term uplift and teams would piece together retrospectively whether the campaign had delivered meaningful value.

That approach has largely given way to a more rigorous focus on measurable impact.

At Now Listen PR, it’s something we see consistently across campaigns. Artists are increasingly focused on engagement quality over raw exposure figures, particularly when planning independent releases. A well-placed feature in a genuinely relevant outlet will often deliver more lasting value than a high-profile placement reaching an audience with no real connection to the music.

Reach remains important. But relevance is what determines whether that reach translates into anything meaningful.

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Spotify Data Is Quietly Influencing Creative Decisions Too

This is the area that makes some musicians most uncomfortable, and understandably so. But it’s happening regardless of how the industry feels about it.

Artists are now routinely examining skip rates, monitoring where listeners drop off and tracking which tracks are being added to personal playlists. Over time, that information influences creative behaviour.

It is audible in the structure of modern releases. Intros are shorter. Runtimes have contracted. Hooks are arriving earlier in the track than they did a decade ago.

This is not a sign that artists have become less creative. It reflects the fact that streaming platforms have fundamentally changed how audiences consume music. Attention patterns shifted, and the data made that shift visible in a way that could no longer be ignored.

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There is, of course, a balance to be maintained. When every creative decision becomes data-led, the music tends to feel engineered rather than genuine, and audiences are perceptive enough to notice. The artists achieving the most sustained success right now tend to be those who use analytics as a point of reference rather than a creative brief.

Data Helps, But It Still Can’t Manufacture Connection

What gets lost in the wider conversation about analytics is that data can only measure response. It cannot manufacture it.

You can optimise release timing, analyse retention graphs and track engagement patterns with considerable precision. But none of that matters if the music itself doesn’t connect with people on an emotional level.

Data can tell you what is happening. It is far less equipped to explain why someone becomes genuinely attached to a track – why a song follows a person around for years, or surfaces at exactly the right moment in their life.

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That remains largely unpredictable. Which is, in many ways, the point.

For all the dashboards, algorithms and audience intelligence now shaping how music is marketed, the music itself is still emotional first. The numbers are simply a reflection of that.

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Why the UK’s AI Buildout Needs to Learn From the Retrofit Model

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Why the UK’s AI Buildout Needs to Learn From the Retrofit Model

Britain has committed £1.5 billion to its next wave of AI infrastructure

The question now isn’t whether the money will be spent — it’s whether it will be spent well.

Across the industry, the default answer to rising compute demand has been to build. Break ground on a greenfield site, lay years of planning and grid connection applications end to end, and hope the facility is ready before the workloads it was designed for become obsolete. It is a model built for a slower era of technology, one where a five-year construction timeline was an inconvenience rather than a competitive death sentence.

However, the default has proven to be outdated.

Samir Tabar, chief executive of the Nasdaq-listed AI infrastructure company WhiteFiber, has spent the past year proving there is a faster and cheaper way in.

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Rather than building from scratch, WhiteFiber has focused on acquiring underutilised industrial sites that already come with the two things a data centre most desperately needs: substantial power capacity and proximity to major metro areas. Its flagship US project, a former textile mill in Madison, North Carolina, was bought for a fraction of the cost of comparable greenfield land and shell development, and converted into a hyperscaler-grade AI campus in a little over a year. The result was validated in the clearest way an infrastructure model can be: a ten-year, roughly $865 million colocation agreement with the European AI hyperscaler Nscale, one of the largest names in the sector’s European expansion.

The economics of that deal are the part the UK should be paying closest attention to.

Tabar’s retrofit approach compressed years off the delivery timeline, converted a fast-moving acquisition into a project institutional lenders were comfortable underwriting, and did it all while sidestepping the cost overruns and planning delays that have become endemic to greenfield data centre construction.

In an industry where the decisive competitive variable is shifting from the size of a campus to the speed at which it can be delivered at uncompromised quality, that is not a marginal advantage. It is the whole game.

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The UK, by contrast, is still leaning heavily on the greenfield playbook, even as it pours fresh capital into AI compute through its AI Growth Zones and national supercomputer commitments.

Grid connection queues remain one of the single biggest bottlenecks to getting new capacity online, and the industrial landscape — much like America’s — is dotted with underused, well-powered sites that a retrofit-first strategy could bring into service in a fraction of the time.

If the UK wants its £1.5 billion to translate into operational AI capacity rather than years of planning applications, the retrofit model Tabar has proven out in North Carolina offers a template worth studying seriously.

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EasyJet expands base at Bristol Airport supporting hundreds of jobs

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The budget airline now operates 90 routes from Bristol

Bristol Airport - newest addition to easyJet’s fleet flies into Bristol Airport - new Airbus 320 joins the airline’s Bristol-based fleet.  Photographer: Michael Lloyd/Staff   Reporter:    Copyright: Bristol News and Media

An easyJet aircraft(Image: Bristol News and Media)

Budget airline easyJet has added an extra aircraft to its base at Bristol Airport in a move it says will support 400 jobs including pilot and cabin crew roles. The A320 Neo plane is the carrier’s 20th at the South West transport hub.

EasyJet said the expansion has enabled it to provide more routes from Bristol including to destinations such as Reus, Thessaloniki, Seville, Cape Verde, Bari and Budapest.

The airline now operates 90 routes from Bristol to 27 countries.

Kevin Doyle, easyJet’s UK Country Manager, said: “We are delighted to have welcomed the arrival of a 20th aircraft and our 13th Neo aircraft at our Bristol base. Our continued commitment and growth in Bristol supports many skilled jobs and plays a vital role in connecting the South West to Europe and beyond.

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“Providing more affordable air travel not only ensures flying remains accessible to the six million passengers who choose to fly with us from Bristol each year, but also drives inbound tourism, bringing visitors and economic benefits to the South West.”

Dave Lees, chief executive of Bristol Airport, said the airport was “especially pleased” to welcome another Airbus A320 Neo.

According to easyJet, Airbus’s Neo aircraft are 20 per cent more fuel efficient per seat as well as 50 per cent quieter than the planes in the rest of the fleet. Neo now make up 65 per cent of the easyJet fleet at Bristol.

“This underpins our commitment to local communities that we are actively encouraging newer, quieter and more fuel-efficient aircraft to Bristol Airport,” said Mr Lees.

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“We’re really proud to be one of easyJet’s biggest European bases, which is so important for providing not only unrivalled choice of destinations, more inbound tourism opportunities, connections and frequency, but more high-quality jobs in our region.”

Earlier this month, US investment giant Apollo agreed to acquire easyJet for £5.7bn in a surprise move that trumped an earlier approach from rival asset manager Castlelake.

The budget airline confirmed it was prepared to accept an all-cash proposal from Apollo, valuing the airline at 714p per share. The carrier said Apollo’s offer “delivers a superior outcome for easyJet shareholders”.

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IBM cuts annual revenue growth forecast as customers prioritize AI infrastructure spending

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IBM cuts annual revenue growth forecast as customers prioritize AI infrastructure spending
IBM cut its annual revenue growth forecast on Wednesday, days after shocking Wall Street with a warning that corporate spending was shifting toward AI-focused data-center gear at the expense of its software and mainframe computers.

The company also missed profit and revenue expectations for the second quarter ended June 30. Executives sought to reassure shareholders that customers prioritized spending on AI in the quarter but were not looking to move away from mainframes in the ‌longer term.

The Armonk, ⁠New York-based ⁠company’s shares dipped marginally in extended trading, following a 2% rise earlier.

CEO Arvind Krishna said last week IBM had “faltered” in adapting and “numerous large deals” had slipped, sending the company’s shares down 25%, its steepest one-day fall in more than a century.

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On the earnings conference call, Krishna said a “majority of what didn’t happen in the second quarter was large capex deals at large clients” and added that about one-third of those deals had now closed in the current third quarter.


“A lot of the demand is deferred, not destroyed,” ⁠Krishna said.
IBM’s ‌forecast spotlights how the scramble for AI hardware has stoked investor fears that companies rushing to secure scarce servers, chips and networking gear could be cutting back on spending on ⁠the wider software sector. IBM now expects 2026 revenue growth between 4% and 5%, down from its previous expectations of more than 5% growth. The midpoint of the forecast is below analysts’ average estimate of a 4.8% rise to $70.77 billion in revenue, according to data compiled by LSEG.

“For the broader software sector, this should be treated as a positive print, with IBM’s software woes more likely to reflect specific IBM-related hardware issues, as management outlined in its investor letter last week,” CFRA analyst Brooks Idlet said.

Revenue from IBM’s Z mainframe, which processes millions of ‌daily transactions across industries such as banking and airlines, slumped 42% in the second quarter, dragging infrastructure revenue down 7% to $3.84 billion.

“That mainframe stack of hardware and transaction processing software impacted IBM’s growth by over five ⁠points in the quarter,” IBM finance chief James Kavanaugh told Reuters. “We were only expecting about a point or two of an impact.”

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He said IBM sees “no evidence of clients moving off a mainframe,” adding that it expects “significant outperformance in the program to continue through the second half.”

Software revenue in the second quarter rose 5% to $7.76 billion but missed an average estimate of $7.88 billion.

The company’s second-quarter revenue ticked up 1% to $17.16 billion, missing estimates of $17.58 billion. IBM reported a net profit of $2.17 billion, a dip from a year earlier, while adjusted profit of $2.93 per share missed an average estimate of $2.97.

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