JPMorgan has raised its year-end target for the S&P 500 to 8,000 from 7,800 points, reflecting growing confidence that the huge investment in artificial intelligence is beginning to translate into stronger corporate revenues. The new target implies around 3.1% upside from the index’s latest close and follows one of the strongest earnings seasons in recent years. This is down to 436 S&P 500 companies having reported second-quarter results, of which 85.1% exceeded analysts’ expectations, well above the long-term average of 68%, according to LSEG.

The clearest evidence of AI capex paying off is emerging among the technology companies driving this investment cycle. Alphabet, Amazon and Microsoft have reported stronger cloud growth, with Google Cloud leading with an 82% increase to $24.8 billion in revenue. Moreover, expanding backlogs and improved visibility over future cash flows are easing concerns that billions of dollars in capital expenditure could fail to generate adequate returns. JPMorgan expects AI-related spending to account for more than half of the S&P 500’s $1.5tn in capital expenditure this year. Although hyperscalers are still expected to record negative free cash flow next year, accelerating customer demand suggests revenues could begin to grow faster than spending.

However, JPMorgan’s bullish outlook does not mean the risks to equities have disappeared. The bank has maintained its forward price-to-earnings target at around 20x, citing higher interest rates, geopolitical risks and substantial equity and debt issuance. With the S&P 500 already up 13.3% this year, the relatively modest 3.1% upside to JPMorgan’s new target suggests that further gains will depend on AI investment continuing to translate into stronger revenues and returns. The market’s next test will therefore be whether the AI boom can move beyond expectations and deliver sustained earnings growth across the wider economy.

- Muthu Ramanathan

Today, Meta released Muse Glimmer, an open-weight AI model, alongside a 6,500-word manifesto from Mark Zuckerberg laying out a vision he calls "AI for everyone." It is the latest step in the most expensive comeback attempt in the technology industry.

The spending has been staggering too. Following the failure of Meta's Llama 4 models last year, Zuckerberg overhauled the company's AI strategy by committing roughly $14 billion to recruit Scale AI's Alexandr Wang and approved individual researcher compensation packages reportedly worth hundreds of millions. The new Meta Superintelligence Labs has since shipped fast: the Muse Spark language model in April, an image model in July, a coding agent this month, and now Glimmer, a compact model built for always-on local agents.

The strategy is a real bet on a different lane. While OpenAI, Anthropic and Google chase enterprise and government contracts, Zuckerberg is pledging free, open models for billions, distributed through Facebook, Instagram and WhatsApp, and argues that widely shared AI is the only way to stop power concentrating in a few institutions. He calls the goal "personal superintelligence," an assistant that knows your world because it is built on it.

However, the drawback is that Meta is still playing catch-up. Its coding model benchmarks a notch below the leaders, several marquee hires have already left, and the open, altruistic framing sits awkwardly beside a new revenue mandate and data arrangements that train Meta's models on users' own activity. Although Meta has bought its way back to the table and picked a genuinely contrarian path, whether that turns millions of users and billions of investment into a lead or merely an expensive second place is the question its investors are now asking.

- Neev Dave

OpenAI and Anthropic account for 43% of worldwide venture investment

Venture capital investment worldwide reached $510 billion in the first half of 2026, according to Crunchbase data, surpassing the $440 billion invested across all of 2025 and marking the highest total ever recorded for a half-year period. 

The increase owes almost entirely to a handful of artificial intelligence companies: OpenAI and Anthropic alone accounted for $217 billion of the total - 43% of every dollar invested in startups globally during the period. 

Concentration was sharper still earlier in the year: AI-sector venture funding reached $255.5 billion in the first quarter alone, eclipsing the entire 2025 AI funding total within a single three-month period, with OpenAI closing a $122 billion round, Anthropic raising $30 billion and xAI securing $20 billion. 

The picture looked markedly different further down the funding stack. Deal counts for vertical AI applications (software built for a single industry) fell to their lowest level since 2018, even as average deal sizes in that category more than doubled year-over-year, pointing to capital consolidating around fewer startups rather than funding the category broadly. 

Liquidity has also returned after a prolonged drought: SpaceX’s $250 billion acquisition of xAI was completed during the half, now standing as the largest AI-related M&A transaction on record. Whether the rebound extends beyond a small circle of frontier AI companies remains the defining question for venture capital heading into the second half of the year.

- Saiee Katarkar

Until next time,

The Long and Short

Markets, Made Sense